Cynthia A. Challener is a contributing editor to Pharmaceutical Technology.

Cynthia A. Challener

Dissolution in the intestinal tract is an essential first step in the delivery of most oral solid-dosage drugs. A high percentage of drug candidates today are, however, considered to be poorly soluble according to the Biopharmaceutical Classification System (BCS). Formulators are challenged to develop delivery mechanisms to overcome these solubility issues. Many excipients can enhance solubility as well. The challenge is to select the right ones for the specific API and dosage form.

	A diverse array of excipients is used for solubility enhancement, including cellulosics, vinylpyrrolidones, acrylates, modified or copolymer variants of these chemistries, and various lipids such as triglycerides. Poorly soluble APIs can also be formulated with carriers such as cyclodextrins to form complexes that can enhance solubility and bioavailability.

	Each of these excipient classes are capable of drug/polymer interactions that stabilize the compound in the desired state (e.g., amorphous state) and deliver it as intended, according to Kevin O’Donnell, R&D manager in pharma excipients at DowDuPont Specialty Products (DuPont) Division. “With the exception of controlled-release systems, these polymers will also be hydrophilic, possibly with pH-dependent dissolution, to improve wettability of the final formulation of the often highly hydrophobic APIs,” he explains.

	Recent excipient introductions into the pharmaceutical market have been focused on overcoming processing limitations, because the formulation of poorly soluble compounds typically requires an enabling manufacturing technology, according to Paula Garcia-Todd, global strategic marketing manager for drug delivery technologies at DuPont Nutrition & Health.

	The rationale for selecting the appropriate excipients for solubility enhancement should be primarily driven by the chemical structure and physico-chemical properties of the API and the target drug load, which together lead to the desired final dosage form, according to Sanjay Konagurthu, senior director of science and innovation in the pharma services group, part of Thermo Fisher Scientific.

	Typical API properties used for selecting the appropriate excipients include aqueous solubility, LogP, LogD, pKa, melting point, glass-transition temperature, organic solubility, thermal stability, precipitation kinetics, chemical stability, and others.

	For example, O’Donnell notes that if the API is not soluble in organic solvents, it is likely that a fusion technology such as hot-melt extrusion (HME) will be used. In that case, excipients amenable to extrusion will be the first to be evaluated. Conversely, if the API is thermally unstable, excipients that are soluble in the same solvents as the API will be evaluated for spray drying.

	“A couple of the most fundamental considerations for developing robust formulations are ensuring that the API has sufficient solubility and stability in the solubility-enhancing excipients. These are the critical properties to overcome a solubility hurdle of the API,” adds Ronak Savla, scientific affairs manager, Catalent.

	Ultimately, formulation choices for excipients are primarily driven by the type of enabling technology used for solubility enhancement, according to Konagurthu. “We need to ensure we choose the right excipients for maintaining the physical and chemical stability of the intermediate(s) as well as the final dosage form,” he says.

	Lipid-based drug delivery systems (LBDDS) are one of the most widely used technologies for solubility enhancement, according to Savla. LBDDS can contain different combinations of oils (triglycerides or mixed glycerides), water-soluble surfactants (e.g., different forms of castor oil and polysorbates), water insoluble surfactants (e.g., oleic acid), and co-solvents (e.g., ethanol, PEG400, and propylene glycol).

	“These excipients solubilize drugs or form emulsions. Therefore, in addition to purity and safety of the excipients, the most important attributes to consider during LBDDS development are the solubility and stability of the drug in the formulation and the minimization of drug precipitation upon contact with gastrointestinal fluid,” explains Savla.

	Amorphous solid dispersions (ASDs) are increasingly used for solubility enhancement. In HME and spray-drying, the API is distributed throughout a polymer network, maintaining the API in a higher-energy amorphous state with greater solubility than its preferred lower-energy crystalline state. “To ensure stability of ASDs, the polymer should not only be compatible with the drug but also be miscible and enhance the supersaturation of the API in aqueous media,” Savla observes.

	A wide range of polymers are used in ASDs, including cellulosics, polyvinyl derivatives, and polymethacrylates. Hygroscopic or acidic polymers that might lead to hydrolysis or acidic degradation are an exception. Various additives such as surfactants, plasticizers, and permeation enhancers are also often employed by formulators.

	The dosage form itself will impact the choice of excipients as well. For oral solid-dosage forms, Garcia-Todd notes that the permitted daily dose of an excipient and the physical properties of the excipient (e.g., many lipids may not be suitable for tablet formulation) must be considered. For non-oral routes of administration, such as implantable formulations, she adds that regulatory or toxicology limitations may exist for an excipient that limits or prevents its use.

	Formulation requires time and resources to create and test different formulations in the laboratory. Modeling and simulation tools hold the promise to improve speed and reduce costs by helping formulators simulate API-polymer interactions and focus their experiments on the polymers that have the most promise, according to Savla. He does note, however, that these modeling and simulation technologies are still in their infancy and there needs to be a continued effort to build the dataset for these models and validate them against in-vitro experiments.

	For Garcia-Todd, modeling and simulation are already useful to some extent. “While modeling and simulation can be useful for eliminating certain excipient classes during excipient selection, they are not yet to the point of identifying a single best option. Often, these systems will identify a number of excipients that are most likely to be successful but it is then up to the formulator to test the set and identify which is indeed most capable of improving drug solubility for a given API,” she says.

	Konagurthu, on the other hand, notes that the speed and performance of computational modeling methods using quantum mechanics (QM) and molecular dynamics (MD) has significantly improved, allowing for rapid in-silico screening of drugs in more complex environments. “To further improve success rates and reduce development time and cost, early consideration of the drug delivery method and formulation approaches should begin in parallel with drug discovery and development programs,” he asserts.

	Thermo Fisher is actively leveraging modeling and simulation tools for excipient selection. The company has developed a novel in-silico approach/platform for identification of the appropriate solubilization technology and excipient selection for solubility enhancement, according to Konagurthu. The platform is designated as Quadrant 2 and is an agnostic approach toward formulation selection of excipients based on computer algorithms that use a combination of calculated descriptors and available experimental physico-chemical properties.

	“Excipient selection and drug loading is accomplished by calculating descriptors, energies of interactions from QM and MD simulations combined with machine learning. These provide the input to an algorithm that provides a rank ordering of recommended excipients and drug loading options,” Konagurthu explains.

	Thermo Fisher uses these simulations in the early phases of the development process to rapidly identify candidate excipients for drugs, predict key experimental properties of the formulations, and determine drug loading and formulation stability. Notably, the company has validated its models with experimental data for more than 175 compounds to a predictive accuracy of greater than 80%, according to Konagurthu.

	Many companies have their own unique protocols for excipient screening/selection for solubility enhancement formulations. “While methods will vary, the common goals will include (for ASDs), identifying the excipients most capable of holding the drug in the amorphous state (e.g., film casting and looking for residual crystallinity); identifying which of those are capable of generating strong supersaturation and maintenance thereof; identifying the potential drug load in the strongest candidates; and analyzing for potential incompatibilities. Additional steps may include evaluation of excipient properties of each candidate excipient in the intended manufacturing method,” O’Donnell explains.

	At Catalent, the first step is screening API solubility, stability, and potential solid-state changes in a panel of common excipients used in FDA-approved products. Based on these results, formulation prototype development with other ingredients (surfactants, co-solvents, etc.) is undertaken. “It is important to keep in mind that the amount of excipient in the formulation is under the maximum allowable potency per dose,” Salva notes.

	Thermo Fisher first uses its Quadrant 2 platform to select an available list of solubility enhancement technologies suitable for the API. The algorithm then identifies candidate excipients for each technology type and predicts factors such as maximum drug loading, stability, and dissolution performance for numerous different excipients. “Based on these results, a significantly reduced number of candidate excipients is generated. The top five to six are selected for experimental feasibility screening using small amounts of API (<1g),” Konagurthu says.

	“Every API is different, and unfortunately there is no silver bullet that is effective for all drugs,” Garcia-Todd asserts. “With each compound, the formulator must identify the best enabling technology and the best excipient concurrently, and often these do not match. Finding the proper balance of performance and manufacturability is crucial early in development to ensure a drug product is effective and does not fail because it cannot be made,” she says. Adds Konagurthu: “The most challenging aspect is to reduce the number of excipients to a manageable level and have a high probability of improving the solubility and bioavailability.”

	What will help ensure success? “First, be material agnostic,” says O’Donnell. Just because an excipient worked in the past does not mean it will be the best choice in all cases. “Second,” he continues, “understand the limitations of your excipients in manufacturing technologies: do not try to force fit an excipient into a technology. Third, solubility enhancement does not guarantee bioavailability enhancement; advance more than one formulation into 

	For Savla, because every drug is unique, it is important to comprehensively characterize the API to understand the challenges (e.g., poor solubility in acidic conditions) and develop potential formulation. It is also important to recognize that excipients work through different mechanisms in different enabling technologies. He also notes that some amount of experimentation is required.

	The first step to take, according to Konagurthu, is identifying the appropriate enabling technology for solubility enhancement based on the API’s physico-chemical properties. Next, it is important to avoid excessive time-consuming empiricism by having a rational selection and screening strategy for excipient selection without relying on “trial-and-error” approaches. Ultimately, he says the goal is to make sound decisions based on balancing the aspects of bioavailability, manufacturability, and stability to develop a robust, commercializable drug product.

Vol. 43, No. 3
	March 2019
	Pages: 22–24

	When referring to this article, please cite it as C. Challener, “Strategic Screening for Solubility Solutions," 

Articles

Understanding the API, delivery mechanism, and excipient functionality is essential to solving drug solubility challenges.


Strategic Screening for Solubility Solutions

Analytical instruments are increasing in sensitivity and accuracy. Pharmaceutical methods applied today generate increasing quantities of data. These data are stored and manipulated using a variety of software platforms from different suppliers. Pharmaceutical scientists must be able to integrate and interpret these data in an efficient manner that ensures reliability, security, and regulatory compliance.

	Today’s modern laboratory is highly dependent on a range of instrumental technologies, all reliant on data output that has to be interpreted, managed, and maintained in a retrievable, secure, and non-corruptible manner, according to Mark Rogers, global technical director at SGS Life Sciences. The volume and complexity of these data make the move to electronic capture inescapable, he adds.

	For many of these techniques, however, the inevitable evolution from paper-based data collection procedures to electronic systems has not been without difficulties. “It may be argued, for example, that the relatively simple process of recovering and reviewing chart recordings from a well-maintained paper archive has advantages over the recovery of data from older software/operating platforms that may have become obsolete, making data difficult to retrieve,” Rogers explains.

	Regulatory considerations have also now become intrinsically linked to the traceability, security, and non-corruptibility of scientific data, again resulting in difficulties with older equipment, he notes. “The electronic modernization of older-but well-established and effective-equipment may be one of the most significant and ongoing challenges,” asserts Rogers.

	In addition, despite advances in the digitalization of analytical data, significant human intervention and manipulation is still required during any decision-making process based on data acquisition. For lot release, once a specification (identify, purity, physical form, etc.) has been established and test methods validated for a drug substance, there are many human intervention steps involved to get from a request for release to fulfilling that request, explains Andrew Anderson, vice-president of innovation and informatics strategy at ACD/Labs. Spectra must be collected and separation analyses performed. The data obtained must be generated as a table, chart, or other picture that describes the results, which must then be compared to reference standards to determine whether they conform or not.

	“Many of these steps cannot be digitized or even easily automated. Bringing data back into the decision-making mechanism is very difficult without specialized informatic tools that handle all different types of data. This challenge is the greatest latent pain for development organizations,” Anderson asserts.

	There will also always be challenges with getting the right data, according to Anderson. “There are trade-offs between project timelines and the data that can possibly be generated and ultimately handled by existing infrastructure,” he explains.

	One example relates to the move to a quality-by-design approach to process development. With this approach comes a geometric expansion in the quantity of data being acquired to characterize a process. Each possible parameter variant requires a data point for the modeling system used to determine the optimum operating conditions.

	In addition, the data itself is becoming more complex. A nuclear magnetic resonance (NMR) spectrum provides a significant amount of detailed information about a given molecule and is therefore attractive for small-molecule API proof-of-structure analysis. Interpretation of this type of spectrum, such as comparison with a reference standard to confirm identity, requires an expert, however. “A method for plant operators to use for determining that a lot spectrum conforms to a standard should be rugged and allow for simple acquisition and validation. Ultraviolet (UV) analysis is one example. Such a method leaves some doubt however; NMR provides more fidelity, so there is a tradeoff between absolute confirmation and practicality,” Anderson observes.

	The complexity of analytical experiments will, in fact, always outpace the ability to implement them in quality processes, he adds. “There are often challenges to implementing more complex analytical techniques in a quality paradigm. All of the aspects of quality assurance are increasing in complexity: software systems and how they handle data, quality practices, standard operating procedures, and test methods. Each of these factors must be considered to ensure that drug products introduced to the market are of the highest quality,” notes Anderson.

	It is not only the volume and complexity of raw data being generated that is the key issue for Marco Galesio, R&D team leader in the analytical chemistry development group at Hovione, but the lack of specific and user-friendly software to treat and interpret these data. “Most of the time there is a lot of relevant data being generated, but due to lack of suitable software and sufficient time, it is not possible to take the most out of it,” he says.

	Biologic drugs pose some additional challenges beyond those associated with chemical APIs. Small molecules have one structure and composition. Because biologic drug substances are produced in cells or microorganisms, their structures and compositions can vary slightly from batch to batch, leading to inherent variability, according to Tiffani A. Manolis, senior director of Agilent Technologies’ global pharma strategic program.

	Added to this variability is the complexity of large-molecule structures, which necessitates the use of a greater number of more complex analytical methodologies, according to Íñigo Rodríguez-Mendieta, technical client manager biopharmaceuticals, SGS Life Sciences. In most cases, specific expertise is required to interpret large-molecule data, notes Constança Cacela, associate director of R&D in the analytical chemistry development group at Hovione.

	The necessity to fully define the relatively complex and diverse structural features of large molecule entities has led to expansion in the variability and sophistication of the analytical tools in the biologics field, according to Rodríguez-Mendieta. “Many of these techniques have traditionally been employed in the academic sector where data interpretation relies heavily on subjective manual review, and this is often difficult to translate to machine-based understanding,” he says. Approaches to digitalization have included automated reference to library data as in the case of circular dichroism (CD) and/or the application of complex algorithms as in the case of mass spectrometry (MS)-based sequencing. “None of these approaches has yet been perfected, however, particularly for large-molecule applications where structural diversity can prove a significant impediment to accurate interpretation,” adds Rodríguez-Mendieta.

	The key challenge lies in the fact that with biologic molecules, identity has various meanings related to structure (primary, secondary, etc.), post-translational modifications (PTMs), etc. “Orthogonal analyses are required to ensure full characterization. Chromatography may be used to determine purity, while other methods must be used to determine the identity (sequence, location of PTMs, etc.). Structural assays are often augmented with behavior immunoassays. All of these data must be ‘assembled’ together to create the complete picture. That can be challenging to do digitally, because orthogonal data are often generated in a variety of vendor formats,” Anderson explains.

	The same issues exist for biosimilar comparability studies, Rodríguez-Mendieta notes. “Results have to be considered holistically, which remains a considerable challenge, as the data can be somewhat contradictory and often produced from a wide range of techniques with instrumentation from multiple manufacturers with different data platforms,” he says.

	Next-generation drug substances can complicate the situation even further. Anderson points to antibody-drug conjugates (ADCs) as an example. “ADCs comprise an antibody, a small-molecule cytotoxic payload, and a linker of some kind, which can be an oligomer or other small to medium-sized component. The dynamic range of MS, NMR, or other instruments must therefore be sufficiently wide to allow analysis of small and large molecules, and of course also validatable,” he explains.

	Separation techniques such as gas chromatography (GC), high-performance liquid chromatography (HPLC), capillary electrophoresis (CE), and gel electrophoresis when coupled to UV, Raman, infrared, and fluorescence do not provide sufficient data per se, and particularly for large molecules, according to Cacela. “Data generated by these techniques must often be validated by more comprehensive techniques such as mass spectrometry,” she notes.

	In general, however, LC–MS methods, especially high-resolution MS (quadrupole time-of-flight [Q-TOF], triple quadrupole, etc.), generate overwhelmingly large data files, according to Manolis. “Data sets are becoming very large and pose challenges to any IT [information technology] infrastructure as they are transmitted across networks for storing and analysis,” she observes.

	An additional challenge is related to data interpretation. The acquisition of MS data occurs in much less time than it takes to interpret it, according to Anderson. “With TOF instruments it is possible to gather detailed spectra in just three minutes, so the technique can be useful for screening experiments or monitoring the progress of a synthetic reaction or cell culture. The data files that result can be a gigabyte in size, which is challenging not only from a hard disc perspective, but for interpretation, which can take much longer,” he comments. Furthermore, deep expertise is required to accurately evaluate and filter the meaningful data, Cacela adds.

	Similarly, the volume of data generated in NMR and surface plasmon resonance analyses can be challenging to manage.

	Another challenge given the volume and complexity of data generated today is the need for some sort of data abstraction in order to be able to efficiently leverage analytical data in the decision-making process. “Very large data sets need to be transformed in some way to make them manageable and interpretable in a practical and timely manner. The difficulty, however, is the potential for loss of information,” asserts Anderson.

	Reduction of data creates risk from a total analysis point of view, he adds. Centroided MS data vs. full-profile MS data is one example. The former involves a mathematical transformation of the data that provides simplification and easier interpretation, but the risk of missing important details must be weighed against that simplification.

	There is a big push, according to Anderson, to find ways to use data in a non-reduced way for more practical interpretations.  One example involves modifying the way signals are acquired. In NMR, for instance, Anderson points to nonuniform sampling, which involves pulsing the sample at nonuniform frequencies and allows the reconstruction of spectra close to what would be obtained with full-frequency pulsing but in a smaller data file.

	There is also a focus on the application of machine learning and artificial intelligence in this area, letting machines identify trends and make observations that humans could probably find but don’t have time to do, according to Anderson.

	A theme underlying all of the above areas of concern is the need for software platforms that enable viewing of data generated by different instruments from different suppliers. “The systems we have today generate huge amounts of data. But these same systems are not necessarily capable of integrating these large data sets and providing researchers with actionable information in a multi-modal view,” Manolis states. While data generation and usability of technologies are improving with better user interfaces and easier-to-use systems and applications, the integration of data sets and connectivity between data sets from different technologies and vendors remains a challenge.

	“Software analysis tools, rather than only gather data, should also be able to analyze and interpret that data and provide information as the output,” asserts Lucia Sousa, associate analytical chemist for R&D in the analytical chemistry development group at Hovione. “Vendors are creating software that interprets data, but even these advanced systems still require great effort from the user. Scientists in the laboratory should have knowledge in their fields of expertise and not need to be experts in software applications as well,” she adds. 

	Throughout pharma discovery, development, and commercial manufacturing, data are acquired and stored on separate and disparate systems that contain both structured and unstructured information, according to Manolis. The challenge is further complicated by collaboration with outsourcing partners, suppliers, distributors, and government agencies that have their own disparate systems. Overcoming these challenges will dramatically improve researchers’ abilities to make faster decisions and will ultimately accelerate drug development and approval, she adds. 

	Analytical manufacturers are working with pharma companies and others to build software solutions that ease these processes. The Agilent data system OpenLab CDS ChemStation Edition, according to Manolis, is the first to support the new Allotrope Data Format (ADF) (allotrope.org), an emerging standard developed by a consortium of pharmaceutical companies.

	“ADF standardizes the collection, exchange, and storage of analytical data captured in laboratory workflows and enables labs to transfer and share that data across platforms,” Manolis explains. “There needs to be continued focus on evolving customer requirements concerning analysis and integration of data sets, compliant solutions for analysis and storage, and the IT infrastructure challenges around large data sets, specifically those generated from high-resolution MS analyses,” she continues. 

	It is an exciting time with respect to advances in data analysis and interpretation, according to Anderson. “Instrument manufacturers and software vendors like ACD/Labs are facing a new paradigm. No longer are we dealing with the integration of monolithic systems through document exchange. Copying and pasting spectra into a word document isn’t good enough any longer. Integration of not only data, but applications is needed to provide a seamless user experience. Decision-making interfaces of the future will be interoperable and able to leverage a variety of heterogeneous and orthogonal data,” he explains.

	 The horizon for software solutions to address pharma customer needs is positive and a fast-moving and competitive space, agrees Manolis. “Broadly speaking, there are many organizations evaluating and using tools that were not designed specifically for pharma but perhaps for business or consumers, and these organizations have been adapting them to their needs. Moving forward, we see these boundaries continuing to blur as solutions are delivered from a variety of software vendors.”

	Pharmaceutical scientists will need to adapt as well. An understanding of data science is becoming essential. “This experience is key for analytical scientists to understand the data and challenge the data with the right questions and subsequent analyses,” Manolis says. “To avoid data silos and facilitate the sharing of data, the expertise gained by the data owner will be invaluable when developing ways to use existing information or to integrate additional data,” she adds.

	Furthermore, implementing end-to- end data integration requires capabilities that include trusted sources of data and documents, robust quality, and maintenance of data integrity. “The objective is to tackle the most important data first to achieve a rapid return on investment. Identifying the right infrastructure will therefore be of paramount importance,” states Manolis.

	Hovione also believes that data science will allow data-driven predictions from big data through modeling and statistical inference. “Data science will allow the extraction of meaningful information for decision making and consequently allow increased efficiency in pharma laboratories,” says Galesio. He does note, however, that many pharma researchers still lack expertise in this field. “Going forward it will be especially relevant to combine both data science and analytical expertise. We believe many companies are investing more and more in this area,” Galesio observes.

	Many pharma organizations are building structures or have built structures in the past 5–10 years specifically supporting data science and analysis, according to Manolis. “We would assume this investment will continue as modalities and data sets continue to increase in complexity,” she concludes.

With higher volumes of analytical date being generated in pharmaceutical processing, digitization and platform integration are becoming increasingly important to implement.

Digitization of Data Analysis and Interpretation

Engineering of protein therapeutics has advanced significantly since the first biologic drugs were introduced. Today, monoclonal antibodies (mAbs) have become one of the predominant forms of protein-based biopharmaceuticals, with humanization and fully human monoclonals contributing to their increasing success. Antibody-drug conjugates are a second-generation version leveraging the attributes of both small and large molecules. Bi/multispecific and fusion proteins are emerging as promising third-generation protein drug substances. Peptides and peptidomimetic therapeutics offer the advantages of mAbs but in smaller molecules that may be formulated for oral delivery. Advanced modeling tools are enabling the rapid engineering of more complex proteins with desirable properties. Companies are also paying close attention to the developability and manufacturability of proteins and considering patient needs at the earliest engineering stages, leading to safer and more effective biologic drugs.

	Fully human monoclonals and mAb humanization

	Fully human mAb therapeutics with fully human sequences have reduced immunogenicity potential and improved safety and efficacy, enabling chronic treatment without liabilities, according to Jennitte Stevens, director of process development at Amgen. Generation of fully human antibodies is achieved in transgenic animals. For instance, mouse cells that produce mAbs have been modified by knocking in human genes and knocking out mouse genes. Amgen’s XenoMouse technology has been used to produce the marketed mAb therapeutics denosumab, erenumab, and evolocumab.

	Recently, more fully human platform technologies have been developed, such as OmniAb (Ligand), Trianni Mouse (Trianni), and huTARG (Innovative Targeting Solutions). “The latter is a fully mammalian technology that generates in-vitro antibody diversity through ex-vivo V(D)J recombination in cultured cells. These technologies enhance both the speed and success of developing antibody therapeutics,” Stevens says.

	Humanization of mAbs is another well-established method to generate therapeutic antibodies when transgenic technology is not available or feasible, according to Stevens. “Humanization techniques using complementary determining regions grafting or phage display have enabled the advancement of numerous antibody therapeutics (such as trastuzumab, pembrolizumab, and romosozumab) to the clinic and ultimately to patients. Humanized antibodies may also have improved safety and immunogenicity profiles, which is a desirable outcome for patients,” she observes.

	Bispecific antibodies are an important emerging area in advancing protein engineering for pharmaceutical products, and several bispecifics based on immunoglobulin scaffolds are currently in clinical development, according to Mark Smythe, founder and currently vice-president of technology for Protagonist Therapeutics.

	“Protein therapeutics traditionally were designed as single receptor/protein antagonists or agonists. But to effectively combat disease, many future drugs will require multiple proteins being agonized or antagonized to achieve efficacy, namely in the immune-oncology and inflammation space,” Stevens explains.

	One example is bispecific T-cell engagers (BiTEs). Blincyto, a BiTE targeting CD3 and CD19, became the first bispecific biologic approved in the US market and demonstrates the impact bispecific molecules can have on treatment of disease, according to Stevens.

	“Ongoing IgG-based modular domain engineering and platform development in multispecifics present great potential to elicit synergistic activities, enhanced therapeutic index (efficacy, selectivity, novel signaling) or safety, effector cell retargeting, half-life extension and/or as a trojan horse as well as improved convenience, all of which can result in significantly improved outcomes for patients,” Stevens asserts.

	One example comes from Alligator Bioscience, a Swedish clinical-stage biotechnology company developing tumor-directed immuno-oncology antibody drugs. In January 2019, the company launched its IgG-like RUBY bispecific antibody format that allows plug-and-play generation of bispecific compounds from any two antibodies. The bispecific antibodies consist of immunoglobulins fused via the C-terminal heavy chains to Fab domains, which are attached via their light chains, allowing for unrestrained dual binding to two targets with a bivalent interaction in a manner similar to the natural antibody-antigen interaction. The result is bispecifics with excellent stability and manufacturability properties, superior binding, and dramatically shortened development timelines, according to the company.

	Bispecifics based on non-immunoglobulin scaffolds that overcome some of the limitations of immunoglobulin scaffolds are also being pursued by multiple developers, including Molecular Partners, Ablynx, and Covagen. More than 100 formats of bispecific/multispecific candidates are being engineered across the industry, many in the oncology space, according to Stevens.

	Peptides and peptidomimetic therapeutics

	Although mAbs have led to the development of many meaningful biotherapeutics and provide the clearest examples of successful protein engineering technology, Smythe notes that they have significant practical limitations in therapeutic use, such as the inability to deliver biologics or peptides by oral administration. “One type of recent advance in peptide engineering has been the design of protein-based therapeutics that can bind the same targets or block the same pathways as clinically validated antibodies, while allowing oral administration. This advance can be seen in drug candidates based on constrained peptides, such as those from Protagonist Therapeutics, and in the formulation design of an oral GLP-1 agonist from Novo Nordisk,” he says.

	For therapeutic applications that do not require effector function, engineering of an IgG scaffold lacking effector function can streamline development and commercialization of such a therapeutic, according Stevens. “Various strategies have been developed recently to eliminate Fc-associated effector binding and functions such as antibody-dependent cell-mediated cytotoxicity and complement dependent cytotoxicity activity,” she observes. For example, Amgen has developed a stable effector functionless IgG platform to eliminate off-target effects while maintaining the stability and half-life expected of a traditional antibody. 

	Advances have not been limited to novel protein formats. New strategies are also being applied to the development of engineered proteins that integrate developability prediction, manufacturability assessment, and quality-by-design early in the process. “This approach is critical to achieving right-first-time outcomes during the development and commercialization cycle of a biologic,” asserts Stevens.

	Amgen has developed a next-generation antibody engineering strategy that enables reliable and efficient identification of pre-candidate leads from early screening lead molecules. “We translate patient needs into protein design requirements during development and engineer in attributes to meet biological performance and molecule stability, which provide improved delivery for desired patient outcomes and improved processing during manufacturing. Incorporating patient needs into molecule designs starts with a translation of the target product profile into a quality target product profile followed by application of these targets during selection and engineering of molecules. This process enables faster and more efficient advancement of novel and effective therapies to patients while improving the overall patient experience,” Stevens explains.

	A combination of structure-based drug design with library approaches has become a powerful tool in protein engineering, according to Stevens. “Merging these approaches enables a focused library design that can yield desired protein characteristics rapidly by eliminating the repeated rounds of screening required in a random library approach. At the same time, it enables exploration of a much wider design space than is possible using pure rational design approaches,” she notes.

	More advances can be expected, too. Continued improvements in 

 approaches (modeling, software, and especially machine learning and artificial intelligence) for the prediction of critical molecule attributes such as aggregation, viscosity, and immunogenicity from primary sequences will significantly increase the success rate, accelerate molecule advancement, and reduce the overall resources required to advance a molecule from the discovery to the clinic, according to Stevens.

	Similarly, miniaturization and high-throughput versions of protein assays will reduce analysis times and enable exploration of wider design spaces. Stevens points to nanofluidic characterization assays for antibody identification and developability assessments as one example.

	Cell-free protein synthesis is also promising, but at this point is limited by the current capabilities in gene synthesis, which serves as a bottleneck for throughput. “Low cost, rapid, and precise gene synthesis will be hugely enabling in this area,” says Stevens.

Vol. 43, No. 2
	February 2019
	Pages: 20–21

	When referring to this article, please cite it as C. Challener, “Advances in Engineering of Protein-Based APIs," 

New platform technologies, advanced modeling tools, and addressing patient needs are important developments.

Advances in Engineering of Protein-Based APIs

	Many pharma organizations are building structures or have built structures in the past 5–10 years specifically supporting data science and analysis, according to Manolis. “We would assume this investment will continue as modalities and data sets continue to increase in complexity,” she concludes. 

Vol. 43, No. 2
	February 2019
	Pages: 16–18, 47

	When referring to this article, please cite it as C. Challener, “Paradigm Shift for Data Analysis and Interpretation," 

Leveraging vast quantities of analytical data requires digitalization and platform integration. 

Paradigm Shift for Data Analysis and Interpretation

Editor's note: An abbreviated version of this article appeared in the January 2019 issue of 

FDA had a very active year in 2018. The agency investigated ways to improve the drug approval process, increase the efficiency of drug development and better incorporate patient voices in the process, increase access for the public to less expensive generics, and develop solutions for the prevention of drug shortages.

	In June 2018, FDA Commissioner Scott Gottlieb issued a statement about a proposal to modernize the agency’s drug review office (1). The proposed changes at the Office of New Drugs in the Center for Drug Evaluation and Research (CDER) were intended to provide its “clinicians and scientists more time, better tools, and greater support to advance the clinical and regulatory principles that the FDA uses to evaluate new drugs for safety and efficacy.”

	Also in June, FDA issued the first of four draft guidance documents intended to inform patients and product developers about rigorous approaches for obtaining and incorporating patient input in product development and how the agency will incorporate this information into its regulatory decision-making (2).

	To speed drug development, FDA announced in October 2018 that the agency is developing technology- and disease-specific regulatory frameworks for innovations that may not have previously had a clear development pathway, including modernization of the agency’s approach to clinical trial design (3). It also issued several guidance documents for newer trial designs and the development of next-generation therapies.

	These changes may have helped-or certainly not hindered-the ability of the agency to review new drug applications. In 2018, CDER had approved 59 novel drugs (4), 13 more than approved in 2017 (5). The following information was sourced from press releases issued by FDA and the drug license holders. A list of 2018 novel drug approvals can be found on the 

	Based on information in FDA and company press releases, approximately half of the new drugs were approved under an expedited review process-Fast Track, Breakthrough Therapy, Priority Review, Accelerated Review-or orphan drug status. These results suggest that both pharma companies and FDA remain committed to leveraging the shorter approval pathways made possible in the 2012 Food and Drug Administration Safety Innovations Act.

	Nearly one-third of the new drugs were granted orphan drug designation, clearly reflecting the shift taking place in the industry away from the development of blockbuster drugs to the development of therapies for rare diseases.

	Despite all of the hype about and investment in biologic drugs, only one quarter of medicines approved in 2018 by FDA were biologic-based drugs.

	In response to concerns about the growing prevalence of drug-resistant bacteria and the ongoing need for medications to treat a variety of infections, FDA has placed an emphasis on approving new antibiotics and antivirals.

	Paratek Pharmaceuticals received approval for its modernized tetracycline antibiotic Nuzyra (omadacycline) for the treatment of adults with community-acquired bacterial pneumonia and acute skin and skin structure infections (6). Nuzyra is specifically designed to overcome tetracycline resistance and exhibits broad-spectrum activity. It is also the first and only once-daily intravenous (IV) and oral antibiotic approved for the treatment of both types of infections. Its use enables physicians to transition patients from IV to oral treatment and potentially reduce hospitalizations. Xerava (eravacycline) from Tetraphase Pharmaceuticals is a novel, broad-spectrum antibiotic approved for the treatment of complicated intra-abdominal infections, the most common infection site in intensive care units (7).

	New antiviral medications approved in 2018 include Shionogi’s Xofluza (baloxavir marboxil) for the treatment of acute uncomplicated influenza (flu), the first new antiviral flu treatment with a novel mechanism of action approved by FDA in nearly 20 years (8); and Tpoxx (tecovirimat), the first drug approved for the treatment of smallpox (9). Tpoxx was developed by SIGA Technologies in conjunction with the US Department of Health and Human Services’ Biomedical Advanced Research and Development Authority (BARDA); SIGA received a Material Threat Medical Countermeasure Priority Review Voucher.

	Four new treatments for HIV patients were also approved by FDA in 2018. Biktarvy (bictegravir 50mg/emtricitabine 200mg/tenofovir alafenamide 25mg, BIC/FTC/TAF) from Gilead Sciences is a once-daily single tablet regimen for the treatment of HIV-1 infection (10); Trogarzo (ibalizumab-uiyk) from TaiMed Biologics is the first drug in a new class of antiretroviral medications that can provide significant benefit to patients who have run out of HIV treatment options (11). Merck’s Delstrigo (doravirine/lamivudine/tenofovir disoproxil fumarate) is a once-daily fixed-dose combination tablet, and Pifeltro (doravirine) is a new non-nucleoside reverse transcriptase inhibitor; both were developed for the treatment of HIV-1 infection in adult patients with no prior antiretroviral treatment experience (12).

	Treatments for rare genetic diseases, all with the orphan drug designation, received approval by FDA. Onpattro (patisiran) infusion from Alnylam Pharmaceuticals is the first FDA-approved treatment for patients with polyneuropathy caused by hATTR and is the first in a new class of drugs referred to as small interfering ribonucleic acid treatments (13). Akcea Therapeutics’ Tegsedi (inotersen), also for the treatment of the polyneuropathy of hereditary transthyretin-mediated amyloidosis in adults, is the first RNA-targeting therapeutic designed to reduce the production of human transthyretin protein (14).

	Takhzyro (lanadelumab) from Shire is a plasma kallikrein inhibitor and the first monocloncal antibody (mAb) approved in the United States to treat patients 12 years and older with types I and II hereditary angioedema, a rare and serious genetic disease that leads to unpredictable episodes of severe swelling in different areas of the body (15). Dompé farmaceutici’s Oxervate (cenegermin) is the first drug approved by FDA for the treatment of neurotrophic keratitis, a rare disease affecting the cornea, providing an alternative to surgical intervention (16).

	Galafold (migalastat) from Amicus Therapeutics is the first oral medication for the treatment of adults with Fabry disease and specifically for patients who have a genetic mutation determined to be responsive to treatment with Galafold based on laboratory data (17). Unlike enzyme replacement therapy, this drug increases the activity of the body’s deficient enzyme.

	Crysvita (burosumab-twza) is the first drug approved for the treatment of x-linked hypophosphatemia, a rare, inherited form of rickets that does not respond to vitamin D therapy (18); Ultragenyx Pharmaceutical received the 14th Rare Pediatric Disease Priority Review Voucher awarded by FDA. Palynziq (pegvaliase-pqpz) from BioMarin Pharmaceutical is a novel enzyme therapy approved for the treatment of adult patients with phenylketonuria, a rare genetic disease, who have uncontrolled concentrations of phenylalanine in their blood even on current treatment (19).

	Treatments for both common and rare cancers were approved by FDA in 2018, including Regeneron Pharmaceuticals’ PD-1 checkpoint inhibitor Libtayo (cemiplimab-rwlc) injection, the first approved treatment for metastatic or locally advanced cutaneous squamous cell carcinoma, the second most common skin cancer (20). Lumoxiti (moxetumomab pasudotox-tdfk) injection from AstraZeneca Pharmaceuticals is the first CD22-directed cytotoxin approved for the treatment of adult patients with relapsed or refractory hairy cell leukemia who have received at least two prior systemic therapies, including treatment with a purine nucleoside analog (21). Kyowa Kirin’s Poteligeo (mogamulizumab-kpkc) injection is the first drug approved by FDA for the treatment of Sézary syndrome, a rare and hard-to-treat type of non-Hodgkin lymphoma (22).

	Erleada (apalutamide) from Janssen Pharmaceutical Companies is the first FDA-approved treatment for non-metastatic, castration-resistant prostate cancer (23). The approval was the first to use the endpoint of metastasis-free survival, measuring the length of time that tumors did not spread to other parts of the body or that death occurred after starting treatment. It was the first participant in FDA’s Clinical Data Summary Pilot Program, an effort to provide stakeholders with more usable information on the clinical evidence supporting drug product approvals.

	Lutathera (lutetium Lu 177 dotatate) from Advanced Accelerator Applications (since acquired by Novartis) is the first radiotherapy approved for the treatment of gastroenteropancreatic neuroendocrine tumors, which affect the pancreas or gastrointestinal tract (24). The drug binds to the somatostatin receptors of tumor cells, enabling its entry and their ultimate destruction.

	In late November, FDA approved Vitrakvi (larotrectinib) from Loxo Oncology for the treatment of adult and pediatric cancer patients with a specific genetic feature, or biomarker, on their tumors. The approval marks the second time FDA has approved a cancer treatment based on a common biomarker across different types of tumors rather than the location in the body where the tumor originated.

	Several other firsts were achieved by FDA in 2018. Approval of the first non-opioid treatment for the management of opioid withdrawal symptoms went to US WorldMeds’ Lucemyra (lofexidine hydrochloride), an oral, selective alpha 2-adrenergic receptor agonist that reduces the release of norepinephrine (25). Epidiolex (cannabidiol) from GW Research for the treatment of seizures associated with Lennox-Gastaut syndrome and Dravet syndrome, two rare and severe forms of epilepsy, is the first FDA-approved drug that contains a purified drug substance derived from marijuana and the first drug approved for the treatment of patients with Dravet syndrome (26).

	AbbVie’s Orilissa (elagolix) is the first FDA-approved oral treatment for the management of moderate to severe pain associated with endometriosis in over a decade and the only oral gonadotropin-releasing hormone antagonist specifically developed for women with moderate to severe endometriosis pain (27).

	FDA also approved new medications for the prevention of migraines. Aimovig (erenumab-aooe) from Amgen is a once-monthly self-injection and the first FDA-approved preventive migraine treatment in a new class of drugs that work by blocking the activity of calcitonin gene-related peptide (28). Teva Pharmaceutical Industries’ Ajovy (fremanezumab-vfrm) injection is the first and only anti-CGRP treatment for the prevention of migraine with quarterly and monthly dosing options (29). Eli Lilly’s Emgality (galcanezumab-gnlm) also received approval.

	Several drugs that received FDA approval in 2018 were targeted therapies, and some were even approved with specific diagnostic tests. Pfizer’s Talzenna (talazoparib), a poly (ADP-ribose) polymerase (PARP) inhibitor, was approved for the treatment of for patients with deleterious or suspected deleterious germline BRCA-mutated, HER2ânegative locally advanced or metastatic breast cancer (30). The BRACAnalysis CDx test from Myriad Genetic Laboratories, Inc. was also approved to identify patients who are eligible for the new drug.

	Agios Pharmaceuticals received approval for Tibsovo (ivosidenib), the first isocitrate dehydrogenase-1 inhibitor, for the treatment of adult patients with relapsed or refractory acute myeloid leukemia (AML) who have a specific genetic mutation (31). Patients must be identified using the FDA-approved RealTime IDH1 Assay from Abbott Laboratories.

	The combination of BRAFTOVI (encorafenib

 and MEKTOVI (binimetinib) from Array BioPharma was approved for the treatment of for patients with unresectable or metastatic melanoma with a BRAF V600E or V600K mutation (32). The mutation must be detected using the FDA-approved THxID BRAF Kit from bioMérieux.

	One interesting trend is the development of new drugs by non-profit organizations, sometimes in collaboration with pharmaceutical companies. Two drugs approved to treat tropical diseases were developed using this approach. The not-for-profit company Medicines Development for Global Health (MDGH), in collaboration with the World Health Organization Special Program for Research and Training in Tropical Diseases, received FDA approval for moxidectin 8 mg oral for the treatment of river blindness, which is caused by the parasite 

(33). It is the first new drug approved for the treatment of river blindness in 20 years. MDGH received a priority review voucher (PRV), a saleable item that enables the owner to receive accelerated review of a new drug application (NDA)-the first not-for-profit company to do so under the tropical disease PRV program.

	Similarly, GlaxoSmithKline (GSK) received a tropical disease PRV for its part in the development of the first new treatment for 

) malaria in more than 60 years (34). Single-dose 

 (tafenoquine) was developed in collaboration with Medicines for Malaria Venture  and received FDA approval for the radical cure (prevention of relapse) of 

 malaria in patients aged 16 years and older who are receiving appropriate antimalarial therapy for acute 

	Two other interesting examples are the first approval of a vaginal ring contraceptive: the Population Council’s Annovera (segesterone acetate and ethinyl estradiol vaginal system) (35); and Omegaven, a fat emulsion manufactured by Fresenius Kabi and demonstrated by researchers at Boston Children’s Hospital to be effective for preventing liver disease associated with parenteral nutrition in children (36).

	Most of the drugs on FDA’s approval docket through early 2019 include treatments for many common conditions, including heart disease, immune deficiency, diabetes, and influenza (37). There are also several treatments for neurological and psychology disorders, such as Parkinson’s disease and depression. Several drugs for pain management are under review, as are treatments for skin infections, glaucoma, breast cancer, and erectile dysfunction. Several new drugs for the treatment of rare cancers are also awaiting FDA decisions.

	Digital health became an increasingly important focus area for FDA in 2018. After launching the Digital Health Innovation Action Plan in 2017, which is seeking to modify the agency’s approach to digital health products (38), FDA formed the internal data science incubator the Information Exchange and Data Transformation (INFORMED) in 2018. The agency has also proposed to create a Center of Excellence for Digital Health in its Fiscal Year 2019 Budget.

	Also in 2018, FDA approved the first medical device that combined a special camera and artificial intelligence to detect greater than a mild level diabetic retinopathy in adults who have diabetes in a primary care setting (39) and permitted the marketing of an artificial intelligence algorithm for aiding providers in detecting wrist fractures (40). Most recently, FDA awarded 

 clearance to Apple’s Series 4 model of the Apple Watch (41).

	FDA Commissioner Scott Gottlieb has indicated that digital technology requires “a reimagination of healthcare delivery” (38). The agency is committed to fostering, not hindering, innovation in digital health technology. Gottlieb hopes the new Center of Excellence will “help establish more efficient regulatory paradigms, consider building new capacity to evaluate and recognize third-party certifiers, and support a cybersecurity unit to complement the advances in software-based devices.”

	From artificial intelligence technologies such as deep learning and natural language processing to smart devices and advances software and apps, digital technologies will clearly play an increasing role in drug and medical device development going forward.

Statement from FDA Commissioner Scott Gottlieb, M.D., on Proposed Modernization of FDA’s Drug Review Office

,” Statement, June 4, 2018.
	2. FDA, “

Statement from FDA Commissioner Scott Gottlieb, M.D., on New Agency Efforts to Advance the Patient Voice in Medical Product Development and FDA Regulatory Decision-Making

,” Statement, June 12, 2018.
	3. FDA, “

Statement by FDA Commissioner Scott Gottlieb, M.D., on FDA’s New Steps to Modernize Drug Development, Improve Efficiency and Promote Innovation of Targeted Therapies

,” Statement, Oct. 15, 2018.
	4. FDA, “

.
	6. Paratek Pharmaceuticals, “Paratek Announces FDA Approval of NUZYRA (Omadacycline),” Press Release, Oct. 2, 2018.
	7. Tetraphase Pharmaceuticals, “Tetraphase Pharmaceuticals Announces FDA Approval of XERAVA (Eravacycline) for Complicated Intra-Abdominal Infections (cIAI),” Press Release, Aug. 27, 2018.
	8. FDA, “FDA Approves New Drug to Treat Influenza,” Press Release, October 24, 2018.
	9. FDA, “FDA Approves the First Drug with an Indication for Treatment of Smallpox,” Press Release, July 13, 2018.
	10. Gilead Sciences, “US Food and Drug Administration Approves Gilead’s Biktarvy (Bictegravir, Emtricitabine, Tenofovir Alafenamide) for Treatment of HIV-1 Infection,” Press Release, Feb. 7, 2018.
	11. FDA, “FDA Approves New HIV Treatment for Patients Who Have Limited Treatment Options,” Press Release, March 6, 2018.
	12. Merck, “FDA Approves Merck’s Delstrigo and Pifeltro to Treat HIV,” Press Release, Aug. 30, 2018.
	13. FDA, “FDA Approves First-Of-Its Kind Targeted RNA-Based Therapy to Treat a Rare Disease,” Press Release, Aug.10, 2018.
	14. Akcea Therapeutics, Inc., “Akcea and Ionis Receive FDA Approval of TEGSEDI™ (inotersen) for the Treatment of the Polyneuropathy of Hereditary Transthyretin-Mediated Amyloidosis in Adults,” Press Release, 


	15. FDA, “FDA Approves New Treatment for Rare Hereditary Disease,” Statement, Aug. 23, 2018.
	16. FDA, “FDA Approves First Drug for Neurotrophic Keratitis, a Rare Eye Disease,” Press Release, August 22, 2018.
	17. FDA, “FDA Approves New Treatment for a Rare Genetic Disorder, Fabry Disease,” Press Release, August 10, 2018.
	18. FDA, “FDA Approves First Therapy for Rare Inherited Form of Rickets, X-Linked Hypophosphatemia,” Press Release, April 17, 2018.
	19. FDA, “FDA Approves a New Treatment For PKU, a Rare and Serious Genetic Disease,” Press Release, May 24, 2018.
	20. FDA, “FDA Approves First Treatment for Advanced Form of the Second Most Common Skin Cancer,” Press Release, September 28, 2018.
	21. FDA, “FDA Approves New Kind of Treatment for Hairy Cell Leukemia,” Sept. 13, 2018.
	22. FDA, “FDA Approves Treatment for Two Rare Types of Non-Hodgkin Lymphoma,” Press Release.
	23. FDA, “FDA Approves New Treatment For a Certain Type of Prostate Cancer Using Novel Clinical Trial Endpoint,” Press Release, Feb. 14, 2018.
	24. FDA, “FDA Approves New Treatment for Certain Digestive Tract Cancer,” Press Release, Jan. 26, 2018.
	25. FDA, “FDA Approves the First Non-Opioid Treatment for Management of Opioid Withdrawal Symptoms in Adults,” Press Release, May 16, 2018.
	26. FDA, “FDA Approves First Drug Comprised of an Active Ingredient Derived from Marijuana to Treat Rare, Severe Forms of Epilepsy,” Press Release, June 25, 2018.
	27. Abbvie, “AbbVie Receives US FDA Approval of ORILISSA (elagolix) for the Management of Moderate to Severe Pain Associated with Endometriosis,” Press Release, July 24, 2018.
	28. FDA, “FDA approves novel preventive treatment for migraine,” Press Release, May 17, 2018.
	29. Teva Pharmaceutical Industries Ltd., “Teva Announces US Approval of AJOVY (fremanezumab-vfrm) Injection, the First and Only Anti-CGRP Treatment with Both Quarterly and Monthly Dosing for the Preventive Treatment of Migraine in Adults,” Press Release, Sep. 14, 2018.
	30. FDA, “FDA Approves Talazoparib for gBRCAm HER2-negative Locally Advanced or Metastatic Breast Cancer,” Statement, October 16, 2018.
	31. FDA, “FDA Approves First Targeted Treatment for Patients with Relapsed or Refractory Acute Myeloid Leukemia Who Have a Certain Genetic Mutation,” Press Release, July 20, 2018.
	32. FDA, “FDA Approves Encorafenib and Binimetinib in Combination for Unresectable or Metastatic Melanoma with BRAF Mutations,” Statement, June 27, 2018.
	33. Medicines Development for Global Health, “US FDA Approves Moxidectin for the Treatment of River Blindness,” Press Release, June 13, 2018.
	34. GSK, “US FDA Approves Krintafel (tafenoquine) for the Radical Cure of 

 Malaria,” Press Release, July 20, 2018.
	35. FDA, “FDA Approves New Vaginal Ring for One Year of Birth Control,” Press Release, Aug. 10, 2018.
	36. Nancy Fliesl, “A Life-Saving Adjustment in IV Nutrition Cleared by the FDA,” Aug.13, 2018.
	37. RTT News, “

tatement from FDA Commissioner Scott Gottlieb, MD, and Center for Devices and Radiological Health Director Jeff Shuren, MD, JD, on Agency Efforts to Work with Tech Industry to Spur Innovation in Digital Health

,” FDA Statement, Sept. 12, 2018.
	39. FDA, “

FDA Permits Marketing of Artificial Intelligence-Based Device to Detect Certain Diabetes-Related Eye Problems

,” Press Release, April 11, 2018. .
	40. FDA, “

FDA Permits Marketing of Artificial Intelligence Algorithm for Aiding Providers in Detecting Wrist Fractures

,” Press Release, May 24, 2018. .
	41. Conor Hale, “New Apple Watch Receives FDA Clearance for Built-in ECG,” FierceBiotech, September 12, 2018.


	Vol. 43, No. 1
	January 2019
	Pages: 30–33

	When referring to this article, please cite it as C. Challener, “FDA Marks Record Year for New Drug Approvals," 

Orphan and cancer drugs continue to lead, but treatments for many common diseases were also approved in 2018. 

FDA Marks Record Year for New Drug Approvals

In bio/pharmaceutical manufacturing, monitoring the bioburden of raw materials, intermediates, drug substances, formulated drug products, and processing environments is essential for ensuring patient safety. Successful bioburden monitoring requires knowledge of both the quantity and identity of detected microbes. The level of information and extent of microbe characterization, and thus the testing protocols, required depend on the specific sample and situation. In cases of potential contamination, knowledge of the identity of a contaminant can help determine its source and thus an appropriate course of action. It is essential, therefore, to implement a microbial identification strategy as part of an effective microbial control program.

	Microbial identification is an important and often overlooked component of bioburden monitoring programs, according to Phil Tuckett, study director at Nelson Laboratories. The intent is to characterize microbes to differentiate one type from another. Identification allows placement of the microbe, depending on the required level of identification and the type of testing employed, into a specific family (genus), species, and/or strain.

	Microbial identifications can be used to provide a platform for thorough investigations, such as for determining the nature of specific contamination events, according to Poonam Bhende, assistant manager at SGS Life Sciences. Microbial identity determination can also be used in a broader manner to provide a rough estimate of the bioburden in a dose of product as an indication of its sterility.

	“It is important to understand not only the numbers of microorganisms present in a product, but also the types of microorganisms they are. Particularly with regard to bioburden reduction strategies, the identity of a microorganism can dictate the best practice for eliminating it,” says Tuckett. Indeed, Bhende notes that through detailed and accurate microbial identification, it is possible to narrow down the source of contamination and take appropriate measures to mitigate the risk for future contamination.

	There are several methods available for microbial identification. They are generally classified as phenotypic or genotypic techniques.

	Phenotypic testing provides data on the physical properties (i.e., morphology, reaction to different chemicals, behavior under certain conditions) that are indicative of a microbe’s genus and in some cases species. “Phenotypic methods, which focus on outward characteristics of an organism-appearance, staining characteristics, biochemical utilization, metabolic requirements, protein analysis-are important components of the microbial characterization level. Given enough of these tests, along with a high level of expertise, a genus/species ID may be obtained,” observes Tuckett. Currently, these methods are most widely used because they tend to be lower in cost and easier to implement. They are, however, generally culture-based and growth dependent, and results can vary with the media and growth conditions that are used. In addition, because many phenotypic tests involve studying the response to treatment with biochemical reagents, repeatability can be an issue.

	Automated systems have been developed to overcome some of these limitations, including Fourier-transform infrared spectroscopy, matrix-assisted laser desorption ionization–time of flight (MALDI–TOF) mass spectrometry, and flow cytometry.

	The industry is, however, moving toward genotypic identification methods due to the growing number of species that are being described every year, according to Tuckett. Genotypic methods involve analysis of the genetic makeup and provide information on the genus, species, and in some cases, the strain of the microbe.

	Analysis of the genome is achieved either through hybridization or sequencing. In hybridization, the extent to which the microbe’s DNA binds with known DNA strands provides information on its structure. Sequencing, generally of the 16S rRNA region, a highly conserved, sufficiently large region present in most bacteria (or the large subunit ribosomal gene in yeasts and molds) is achieved using automated blot technology or polymerase chain reaction (PCR) approaches. Importantly, genotypic testing is not affected by culture or media conditions. “As technology becomes cheaper and more available, whole genome sequencing may provide accurate species and strain identifications,” Tuckett states.

	Separately, the detection and identification of endotoxins indicates the presence of gram-negative bacteria. “Contamination with high levels of endotoxin can be fatal, so accurate results are vital,” asserts Bhende.

	Microbial identification, according to Pia Darker, global senior product manager for the pharmaceutical analytics division of Thermo Fisher Scientific, is most often the end point of different microbiological tests, such as out-of-specification bioburden, failed sterility tests, excursions from environmental monitoring, etc.

	The strategy for identification will depend on the origin of the test samples, as well as the microbial identification method, both of which depend on the overall microbial test strategy. “The first thing to consider is what level of identification is appropriate, and that depends on what the data will be used for,” adds Tuckett.

	There are three basic levels of identification: microbial characterization, genus/species identification, and bacterial strain typing. “For tracking and trending of bioburden levels only, microbial characterization may be sufficient, such as descriptions of the colonies and cells as well as gram staining and other descriptive microbiological assays,” he notes. Such characterization requires a certain level of expertise because appearances can be variable and many characteristics of microorganisms change over time. Given the inherent subjectivity of some of these tests, Tuckett strongly recommends that genus/species identification be performed for at least the overall three to five most common organisms.

	In situations where action/alert levels are exceeded or when contamination events are encountered, genus/species level identification is more appropriate. “Since microbial identification is used to understand the source of contamination, it is important for the identification method to give an accurate species identification in order to implement appropriate corrective actions and preventative actions (CAPA). Implementation of the appropriate CAPA will prevent the re-occurrence of microbial contamination and reduce the risk of quality issues in the manufacturing process,” Darker comments.

	Species identification is also an essential part of testing for objectionable organisms (

 62 testing), according to Tuckett, because mere characterization can sometimes be insufficient to rule out specific species.

	At SGS, most clients ask for species-level identification. “Species-level identification helps us to eliminate the risk of an antibiotic-resistant pathogen becoming prevalent if a new strain is observed that cannot be eliminated through cleaning by disinfectant. Additionally, seasonal change can see a change in bioburden levels which need to be identified,” says Bhende.

	When investigations are being conducted to determine if multiple contaminants are of the same source, bacterial strain typing is necessary. “This testing reveals if different isolates come from the same strain or source, which cannot be determined from species level identification methods,” Tuckett explains.

	An effective microbial identification strategy, according to Darker, results in an appropriate CAPA to reduce any risk of microbial contamination and in the event of microbial contamination enables the determination of the root cause of the contamination. “In essence, if CAPA has been put in place and it mitigates any further risk to product quality and patient safety, then the microbial identification strategy was effective,” she states.

	For Tuckett, an effective microbial identification strategy is one that provides meaningful data pertinent to the given situation and draws upon sufficient resources to ensure the identification is as accurate as possible. “The basic principle behind microbial identification is comparison of the characteristics of an unknown organism to those of a known organism. The more that is known about the known organism, the better the comparisons can be. When genotypic data [are] analyzed, [they are] generally compared to a library or database of known DNA sequences and [are] therefore only as accurate as the database [they draw] upon. An extremely limited database may provide inaccurate identifications,” he explains. In addition, methods based on automated identification software may be inadequate for the intended use if a high number of “unidentified” results are obtained.

	An ineffective strategy is also one for which a CAPA cannot be implemented to stop the reoccurrence of contamination by an identified microbe, according to Bhende. Therefore, as with bioburden and environmental monitoring programs, continuous evaluation and assessment of microbial identification strategies are essential. “As compendial requirements change, and as new technologies become available, identification procedures should be revaluated to ensure they are sufficient for their intended purpose. If a specific identification method doesn’t yield adequate results, alternate methods should be considered,” asserts Tuckett.

	For clients of SGS, Bhende also recommends for critical microbial identification applications the establishment and maintenance of a database logging the trending data for locations and accurate identifications. “This information can be used to identify early on any potential patterns of contamination that need to be addressed,” she says.

Vol. 42, No. 12
	December 2018
	Pages: 44–45

	When referring to this article, please cite it as C. Challener, “Microbial Identification Strategies for Bioburden Control," 

Microbial identity data can be critical for determining contamination sources.