Behind the Headlines Episode 27

Ask the Expert

Small Molecules, APIs, and Excipients—Trends, Challenges, and Opportunities

Drug Digest September 2025

Artificial intelligence, machine learning, and novel instruments are helping drug developers.

Enhancing Bioanalysis and Drug Development with Advanced Tools and Technologies

J.P. Morgan Report Lists Biologics, Obesity, China

Top Trends Reshaping Pharma R&D

Feliza Mirasol is the science editor for 

Chris Spivey is director of Industry Relations and Strategic Partnership, MJH Life Sciences.

The bio/pharma industry is building on the small successes of continuous manufacturing (CM) for the advanced manufacture of bio/pharmaceuticals. With FDA throwing its support behind CM as part of a bigger initiative to progress advanced technologies for biopharma manufacturing, it remains to be seen whether CM technologies will see an uptick in adoption within the industry. In this episode of 

 editors Chris Spivey and Feliza Mirasol discuss with industry experts the advantages and savings that CM may offer as well as the very real obstacles that might make a fully continuous process not feasible, especially in biologics manufacturing.

, owner of Pharmaceutical Engineering Solutions, is a consultant to the pharmaceutical industry working at the interface of technology, R&D, manufacturing, and corporate strategy. He spent nearly 40 years in big pharma, working for Merck, Bristol Myers Squibb (BMS), and Janssen, a Johnson & Johnson company. At Merck and BMS he worked in R&D, rising to vice-president of Process Development at BMS. During those 28 years he was lucky to work on numerous important compounds that went to market, including Primaxin, Mevacor, Proscar, Crixivan , Reyetaz, Entecavir, Muraglitazar, Sprycel, Onglyza (through FDA’s Quality by Design pilot program), Apixiban, Dapagliflozin, and Brivanib.At Janssen, he spent more than 10 years working on manufacturing technology, focusing on integrating data analytics, sensors and models to realize real-time quality awareness and real-time release when possible, along with continuous manufacturing and other manufacturing modalities, covering small molecules, monoclonal antibodies, vaccines, and cell and gene therapy.

 is faculty of the Department of Chemical and Biochemical Engineering, Rutgers University, NJ, and director of pharmaceutical systems engineering. He is the recipient of the prestigious European Federation of Chemical Engineering (EFCE) Excellence Award. His research focus is continuous manufacturing of drug substance and product. He is principal investigator (PI)/co-PI of several projects funded by FDA, National Science Foundation, and companies. He has published more than 75 papers, edited one pharmaceutical systems engineering book published by Elsevier, written more than 12 book chapters, and presented at more than 130 conferences. He is actively serving as a journal editorial board member, and conference session chair.

This episode of Drug Digest is sponsored by:

Drug Digest is a tech talk video series with the 

 editors, who interview industry experts to discuss the emerging opportunities, obstacles, and advances in the pharmaceutical and biopharmaceutical industry for the research, development, formulation, analysis, upstream and downstream processing, manufacturing, supply chain, and packaging of drug products.

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In this episode of Drug Digest, Pharmaceutical Technology editors discuss the advantages and savings that continuous manufacturing may offer as well as the very real obstacles that might make a fully continuous process not feasible, especially in biologics manufacturing.

Drug Digest: Advancements in the Implementation of Continuous Manufacturing

Chris Spivey, editorial director, speaks with Vibha Jawa, executive director at Bristol Myers Squibb, on foreign epitopes recognition in what should be fully human antibody therapies. Can HLA genotyping show which binding targets will be most effective per individual patient, or per T cell response predictor in terms of a reverse translation in the clinic? A tangent from our 

focused on High Titer Vector Producing Cells.

Articles

Vibha Jawa, executive director at Bristol Myers Squibb, discusses foreign epitopes recognition from what should be fully human antibody therapies.

Exploring Foreign Epitopes Recogniton in Personalized Medicines with Vibha Jawa

Hovione and H&T Presspart have partnered to advance the development of Presspart’s Sunriser Capsule-based Dry Powder Inhaler platform. The companies plan to work together to develop the Sunriser Dry Powder Inhaler, which is flexible enough to address the challenges of carrier-based and spray-dried engineered formulations, according to the press release.

A part of the development agreement finds Hovione being an exclusive partner with Presspart to use the Sunriser device in engineered formulations for dry powder inhalation. Additionally, Presspart will still be responsible for the manufacturing of the Sunriser device.

"New inhalable therapies are often requiring delivery of higher doses of cohesive and sensitive powders. Our priority is to ensure maximum efficiency in delivering these drugs to the right locations in the lung,” said Jean-Luc Herbeaux, PhD, CEO of Hovione, in a press release. “We are thrilled to expand our current partnership with Presspart and combine our expertise in the fields of engineered particles and inhalers for the benefit of our customers and patients.”

Presspart will still be responsible for the manufacturing of the Sunriser device.

Hovione and H&T Presspart Extend Partnership for Dry Powder Inhalation Formulation Delivery 

Arranta Bio signed a contract with the Massachusetts Institute of Technology (MIT) on April 28, 2023 to develop a continuous manufacturing technology for messenger RNA (mRNA) therapeutics. The contract is part of FDA’s initiative to have a fully integrated, continuous manufacturing production line for mRNA vaccines.

A three-year project, the plan is set to start the deployment of mRNA vaccines for rapid response against future pandemics and novel mRNA therapeutics to patients around the world. Additionally, mRNA therapeutics are being researched to support the fight against rare diseases, infectious viruses, and cancers.

Current challenges are planned to be addressed in the project for the continuous manufacturing of mRNA therapeutics. Under the terms of the agreement, FDA will directly support and inform the advances to enable Arranta Bio and MIT to push the boundaries of current manufacturing and testing processes, according to the press release.

“We are proud to be working with MIT on this ground-breaking FDA initiative to be forward thinkers and push the boundaries of biologics manufacturing. Our work can enable new vaccines and therapies to be deployed quickly and be economically viable for patients in need,” Marc Funk, CEO of Recipharm, said in a press release. “This project is yet another step towards our vision to be the CDMO of choice, for the benefit of patients.”

mRNA therapeutics are being researched to support the fight against rare diseases, infectious viruses, and cancers.

Arranta Bio Signs Contract with MIT for Rapid mRNA Manufacturing Therapeutics

With the explosion of RNA-based therapeutics on the scene, development projects are ramping up to bring these and other nucleic acid-based therapeutics to market. But what exactly are nucleic acid-based drugs and what advantages do they hold over conventional therapeutics (biologics and small-molecule)?

According to Carl Schoellhammer, PhD, principal at DeciBio Consulting, a US-based life science strategy consulting firm, nucleic acid-based therapeutics are drugs that are made up of a string of nucleotides; these include DNA and RNA-based medicines. These types of therapeutics can act at the genetic level to potentially correct or restore healthy function at the level of a patient’s genes.

Vasant Jadhav, PhD, senior vice-president of Research and head of the RNAi Platform group at Alnylam Pharmaceuticals adds that a common feature of nucleic acid-based therapies is that they are “programmable” drugs; a nucleic acid sequence provides the “code” for the intended target. Examples of approved nucleic acid-based therapies include RNA interference (RNAi), antisense oligonucleotides (ASOs), and the now-familiar messenger RNA (mRNA) therapeutics.

RNAi therapeutics utilize a post-transcriptional gene silencing mechanism in which the active ingredient is double stranded short interfering RNA (siRNA). The siRNA targets and degrades mRNA encoded by a disease-causing or disease-associated gene, explains Jadhav. “RNAi therapeutics leverage a naturally occurring protein complex, called RISC [RNA-induced silencing complex], to accomplish gene silencing,” he states.

Meanwhile, ASOs, also a gene silencing medicine, are composed of single-stranded oligonucleotides that hybridize to target RNA and degrade it by “either recruiting RNAseH [ribonuclease H] (so called gapmer design) or modulate splicing to produce desired mRNA (so called splice switching olignucleotides),” according to Jadhav.

Finally, as has been seen with the COVID-19 vaccines, mRNA therapeutics are experimental genetic medicines in which the mRNA itself is the therapeutic entity; it is introduced with the aim of expressing a functional/therapeutic protein or antigen. However, there are currently no approved mRNA therapeutics outside of the COVID-19 vaccines, Jadhav observes.

The COVID-19 vaccines are currently the most well-known type of medicine that utilizes a nucleic acid-based active ingredient (i.e., mRNA). However, as described previously, nucleic acid molecules can be used for other types of medicines (e.g., as gene-silencing medicines).

Schoellhammer emphasizes the fact that nucleic acid-based therapeutics “are a powerful set of medicines with the capacity to turn signals on, or off, at a genetic level.” He points out that there are well over 10 nucleic acid-based therapeutics that are approved by regulators. “These medicines are, broadly speaking, divided by the action they take in the body to either turn signals on or off,” he states.

ASOs, as well as siRNAs, for example, target genes to turn them off or limit their expression. And while most of these approved nucleic acid-based therapeutics are for rare diseases (i.e., small patient population), some have been indicated for vast patient populations: Schoellhammer points to a Novartis product, Leqvio (inclisiran), which received approval by FDA for treating a type of high cholesterol in late 2021 (1).

Inclisiran, Schoellhammer explains, is a siRNA medicine that shuts off a signal in the liver, leading to a lowering of lipids. While it is currently approved for a subsegment of individuals with high cholesterol, he expects that the therapeutic could in the future be applied to anyone with high cholesterol, therefore making these medicines mainstream.

“On the other end of these therapies sits mRNA, which tells the body to produce, or turn on, specific proteins that the mRNA encodes for. [Messenger] RNA is like a blueprint, telling our cells how to make certain proteins. If a certain protein is desired, the corresponding mRNA can be made and delivered so the body will produce it,” Schoellhammer adds.

This is how the COVID mRNA vaccine operates; it is a sequence that encodes for a small fragment of the spike protein in the SARS-CoV-2 virus, for example. “When our body’s cells produce this small protein fragment, they recognize it as foreign, and produce an immune response, just as a traditional vaccine does,” Schoellhammer says.

“The pandemic demonstrated the power of this therapeutic and interest has flourished, with 100s of companies working to create new mRNA-based medicines and well over 200 public programs in development,” Schoellhammer continues. “These programs are tackling a diverse set of applications, ranging from oncology through the development of immune-stimulating treatments to help fight the cancer, to other indications leveraging CRISPR [clustered regularly interspaced short palindromic repeats]-based editing whereby the mRNA encodes for the CRISPR machinery.”

Nucleic acid-based therapeutics hold a definite advantage over conventional biologics or traditional small-molecule APIs. According to Schoellhammer, one of the greatest benefits of nucleic acid-based medicines is their specificity.

“In the case of those that turn off signals, they must find and bind with the exact complementary sequence in our body to turn it off. This means that other genetic signals can be unaffected. Similarly, for mRNA, the sequence, and therefore the protein it encodes for, is controlled. These features greatly limit any off-target effects that are often seen with small molecules or biologics,” Schoellhammer states.

Compared to small molecules and monoclonal antibodies, nucleic acid medicines, such as RNAi therapeutics work “upstream,” asserts Jadhav, treating diseases at their genetic source—that is, at the RNA/transcript level—rather than by addressing the symptoms/manifestations of the disease. Furthermore, Jadhav adds, “small-molecule drugs and monoclonal antibodies have inherent limitations when it comes to the speed with which they can be developed and the type and breadth of diseases they can be used to treat.”

Jadhav points out that the development of small molecules is an arduous process that relies on understanding the structure of the target disease-causing or disease-associated protein (vs. the genetic sequence that encodes that protein). “Oftentimes the structure of the protein is not known and needs to be solved. Identification of the right small molecule requires screening large libraries of chemical compounds to identify a candidate that can interact with the target protein in a ‘lock and key’ fashion. This is a painstaking process that requires extensive trial and error to achieve efficacy, tolerability, and safety,” he emphasizes.

As far as biologics such as antibodies are concerned, Jadhav explains that, while antibodies as a class of medicines have enjoyed much therapeutic success in the past decade, one of the drawbacks here is the inability to access and act on intracellular protein targets. “In contrast to monoclonal antibodies, nucleic acid medicines, such as RNAi therapeutics, can act on disease-causing or disease-associated proteins that are expressed both on the inside and outside of the cell,” he explains.

Meanwhile, Schoellhammer points out a limitation in nucleic acid-based therapeutic development: nucleic acid-based medicines are difficult to deliver, which is a drawback. To work, he specifies, they must be taken up by the right cell in the right place in the body. At the same time, nucleicacid-based medicines are extremely delicate and susceptible to being destroyed in the bloodstream.

“While this can somewhat limit the indications that scientists are using these medicines to treat, it further helps improve these medicines’ specificity and lack of off-target effects. For example, if one uses an siRNA therapeutic to ‘silence’ a target, dosing someone with more of that siRNA should have little effect. This is not the case for small molecules, such as aspirin, where taking more of it could eventually lead to significant, negative side effects,” Schoellhammer says.

Jadhav, meanwhile, explains that nucleic acid-based therapeutics, such as RNAi-based medicines, leverage a platform technology that gives rise to consistent and predictable drug properties. “This is not the case for small molecules, where each individual small molecule compound is completely unique, both in terms of its design elements and its profile as a drug candidate,” he states.

Development of nucleic acid-based therapeutics supports the bio/pharma industry’s shift to precision medicine. For instance, there are examples of nucleic acid-based medicines (e.g., RNAi therapeutics) that are approved to treat rare and ultra-rare genetic diseases for which there were no previously available therapeutic options, points out Jadhav. He has observed the therapeutic landscape of rare diseases dramatically evolve in large part due to the development and availability of genetic medicines, which now have the potential to help patients with more common diseases for which treatment options are limited or inadequate.

Schoellhammer says that, because these medicines are based on genetic sequences, they are highly specific. They can be used to treat rare diseases that are caused by a mutation in our genes. He points out that Biogen’s Spinraza (nusinersen), an antisense therapy for treating spinal muscular atrophy, was a significant accomplishment that has drastically improved the quality of life in patients for whom the disease often presents in newborns and is fatal by age two.

“Beyond presently approved nucleic acid medicines, companies are working on using these therapeutics in combination with CRISPR machinery to enable highly precise edits to genetic signals in patients. In theory, this could one day be used to target a drug for a unique individual,” says Schoellhammer.

Adding to the complex tapestry of nucleic acid-based therapeutics are the different moieties, or species of molecule, within the nucleic acid space. According to Schoellhammer, there are several different types based on their action. Within ASO therapies, for example, there are a variety of strategies to control the “degree” of silencing. There are certain therapeutics, such as Spinraza, for example, that are termed “exon-skipping” because, rather than telling the body to turn off a gene completely, these therapeutics instruct the body to skip only a certain part of a gene when producing the corresponding signal, Schoellhammer explains.

He also emphasizes the existence of microRNA (miRNA), which can have a similar effect to that of silencing therapies, guide RNAs (gRNA), which are used to target a desired gene sequence in the body for editing using CRISPR machinery, and, finally, certain types of RNA medicines that utilize naturally occurring machinery in the body to elicit an editing effect on defective genes. The latter is referred to as transfer RNA (tRNA).

“Beyond this, there is an almost endless further segmentation based on chemical modifications made to the nucleic acid therapy to make it more resilient to degradation by our body or make it more efficient in eliciting its desired effect,” Schoellhammer concludes.

1. Novartis. FDA Approves Novartis Leqvio (inclisiran), First-in-Class siRNA to Lower Cholesterol and Keep it Low with Two Doses a Year. Press Release, Dec. 22, 2021.

The market potential of nucleic acid-based therapies have been pushed into the spotlight following the success of the COVID-19 vaccines.



Ramping Up Nucleic Acid Therapy Development

Analyzing extractables and leachables (E&L) is paramount to ensuring the safety of a drug product and determining any toxicological risks. Examining extractables can help identify potential risks of leachables contaminating or affecting the quality of a drug product. Extractables can be extracted through the use of solvents under certain extraction conditions or can be forced out with high heat without solvents. Extractables may be potential leachables, but not all extractables leach into drug products. Leachables migrate from the container into the drug product or directly to the patients under normal storage or use (1).

Potential sources of leachables include primary packaging components, secondary packaging components, intermediate manufacturing components, or APIs. There are also E&L that can be introduced from the component molding process and can end up becoming a leachable, such as mold release agents or lubricants (1).

Various regulatory guidelines have been published due to the potential safety risks that leachables pose. FDA published a guidance included in the 

 Title 21 that highlights guidelines on drug product containers and closures, such as:

“Drug product containers and closures must not be reactive, additive, or absorptive so as to alter the safety, identity, strength, quality, or purity of the drug beyond the official or established requirements.

“Container closure systems must provide adequate protection against foreseeable external factors in storage and use that can cause deterioration or contamination of the drug product.

“Drug product containers and closures must be clean and, where indicated by the nature of the drug, sterilized and processed to remove pyrogenic properties to assure that they are suitable for their intended use. Such depyrogenation processes must be validated,” (2).

 General Chapter <665> Plastic Components and Systems Used to Manufacture Pharmaceutical Drug Products and Biopharmaceutical Drug Substances and Products in 2022, which will come into effect in 2026 (3). The document highlights analytical methods of risk assessment of E&L, including biologic drugs.

The Product Quality Research Institute (PQRI) published two industry guidance documents, titled 

Safety Threshold and Best Practices for Extractables and Leachables in Orally Inhaled and Nasal Drug Products

Safety Thresholds and Best Demonstrated Practices for Extractables and Leachables in Parenteral Drug Products (Intravenous, Subcutaneous, and Intramuscular)

 (5) that highlight industrial details on how E&L assessments should be performed. The combination of both regulatory and industrial guidance documents provides a fleshed-out guideline for E&L analysis.

Differences between small- and large-molecule drugs

Leachables can interact with small-molecule and large-molecule drugs in different ways, which is a key consideration when testing for E&L in biologics versus small molecules. Biologics can be immunogenic, and a leachable may interact with a protein and trigger an immune response (6). The efficacy of a biologic drug may also potentially be reduced through interactions of leachables with drug molecules through post-translational modification biochemical reactions, such as oxidation, aggregation, or unfolding, explained Lester Taylor, pharma marketing manager at Agilent (7).

Biologic drugs are sensitive and complex. Extractables or potential leachables that may migrate into a drug product have the potential to interact, and therefore, affect the product quality, safety, or stability, explained Fran DeGrazio, vice-president, global scientific affairs and technical services, West Pharma. Additionally, large molecules have greater surface areas, and interactivity can lead to conformational modifications and other interactions that may impact product quality (7).

A main concern for leachables in small-molecule drugs is the specific toxicity/genotoxicity profiles, said Dr. Wayland Rushing, senior scientific advisor at ABC Laboratories. However, with biologics, there is also the concern of the ability of the leachable to interact with the biologic product itself. Many biologics are very sensitive to metal content. As a result, additional monitoring of the metal content may be required (8).

Key components such as semi-volatile organic compounds, non-volatile organic compounds, volatile organic compounds, and metals can be identified during an E&L study. For extractable studies, exaggerated conditions are often used to emulate a “worst-case scenario,” and the data are used to help determine what further studies are needed to mitigate future risks. Examples of analytical techniques used to detect E&L include gas chromatography mass spectrometry, liquid chromatography mass spectrometry, and inductively coupled plasma-mass spectrometry (9). Taking these differences into consideration can help identify the right tests to use for detecting E&L.

1. Yu, X., and Wood, D. Analytical Testing—Extractables and Leachables
Testing for Pharmaceutical Products. 

2. CFR Title 21, 211.94 (Government Printing Office, Washington, DC).

3. USP. General Chapter <665>, Plastic Components and Systems Used to Manufacture Pharmacueitcal Drug Products and Biopharmaceutical Drug Substances and Products.

 Safety Threshold and Best Practices for Extractables and Leachables in Orally Inhaled and Nasal Drug Products.

 Safety Thresholds and Best Demonstrated Practices for Extractables and Leachables in Parenteral Drug Products (Intravenous, Subcutaneous, and Intramuscular).

6. Moffatt, F. Extractables and Leachables in Pharma-A Serious Issue. (Solvias, accessed March 9, 2023).

7. Siew, A. E&L Risk Assessment for Biologic Drug Products. 

8. Hernandez, R. Special Considerations for Extractables and Leachables Testing in Biological Products. 

9. Thermo Fisher Scientific. Extractables and Leachables: Regulatory Requirements for Vaccine and Biologic Products. (Thermo Fisher Scientific,

E&L analytical testing methods can be determined through pointed consideration of the differences small- and large-molecule drug products.

E&L Analytical Testing Considerations

Digitalization, artificial intelligence (AI), and machine learning (ML) are several of the major tools being used in the bio/pharmaceutical industry today to implement significant leaps in optimization (e.g., reducing costs, shortening timelines, streamlining processes, improving product quality, etc.). Importantly, these tools are being used early in the drug development cycle, from R&D/drug discovery through to clinical-phase development, and then onward in commercial manufacture. A closer look at the implementation of these tools can shed light on the importance of smart drug development in the early discovery phase. For instance, how does using “smart” tools have an impact on the development process going into the clinical phases?

The existing drug development paradigm is based on moving through several stages, sequentially, says Jo Varshney, PhD, founder and CEO of VeriSIM Life, a US-based company specializing in the use of advanced AI and ML techniques for drug discovery and development. Drug development moves from the identification of a disease or condition target to validating a safe and effective drug candidate in human clinical trials, she notes.

“This paradigm suffers from tremendous waste and cost. Passing from one stage-gate to the next is a siloed process where data [are] often not shared and poor proxies define success for human biology—especially animals,” Varshney remarks.

Smart drug development re-imagines the traditional drug development process by allowing for design and validation early in discovery through the use of better models of human biology and more comprehensive data. This allows for the process to be “parallelized,” where, typically, steps such as dosing or formulation can be factored in conjunction with hit-to-lead selection, Varshney notes. “Smart drug development quickly identifies dead-end outcomes so you can course correct before investing in heavy experimentation, which saves time and costs, getting better drugs to patients faster,” she emphasizes.

“‘Smart’ drug development has always been with us,” says Grant Wishart, PhD, senior director, Small Molecule Drug Discovery and Logica Lead, Charles River Laboratories. Wishart points out that the bio/pharma industry has generated knowledge from past experiences and developed and leveraged new technologies to bring new medicines and safer medicines to patients for increasingly complex diseases.

“From rational approaches in the 1960s pioneered by the Scottish pharmacologist, Sir James Black, to computational structure-based design emerging in the 1980s—but perhaps not fulfilling its potential until the early 2000s—there have been many ‘smart’ enhancements to drug discovery and development,” Wishart explains. “Each of these has influenced and advanced what we do to a greater or lesser extent.”

Wishart also points out that organizations continuously strive for “smarter” drug development to reduce discovery timelines and increase certainty in clinical progression. “Today we are at the intersection of advances in data generation, automation, and advanced computation, which come together to offer potential step changes in how we discover and develop drugs of the future,” he remarks.

Digitalization is a major trend in the bio/pharm industry today. Advances in digitalization and other tools have allowed the industry to organize and connect data sets as well as set up more efficient workflows, says Wishart. Smart tools such as digitalization have also allowed the industry to connect disparate data sets from data management systems and instruments across the continuum.

According to Wishart, this connectivity helps the industry to manage information along individual programs. Moreover, it also helps in the aggregation of data to progress ML/AI modeling toward better prediction and assistive tools, he says.

“By doing this, we also have the opportunity to reduce the overall timelines for researchers to match data sets shared from various partners across the ecosystem, including academia, CROs [contract research organizations], and CDMOs [contract development and manufacturing organizations],” Wishart states. “Today, scientists spend a tremendous amount of time doing this, and we envision a world where there is strong interoperability of data between organizations across all phases of drug discovery.”

Meanwhile, Varshney emphasizes the point that smart drug development is dependent on digitalization. She explains that in-silico-based approaches, whether labeled “Model Informed Drug Development” or “digital twin,” bridge the gap between human biological process and understanding those processes by leveraging tremendous amounts of data from existing scientific resources and custom-developed assays.

“Digitalization enables the conversion of analog data for the purposes of complex analysis and machine learning. This opens the door to a high-powered computational understanding of biological processes and predictions about how drugs will interact with them,” Varshney states. She further adds that digitalization also reduces the “black box” of animal testing, in which experiments often succeed only to fail inexplicably in humans.

Tools such as AI, automation, ML, and digitalization are already being utilized for bio/pharmaceutical manufacturing processes, but how are they being leveraged in the R&D and drug discovery/drug screening phases?

According to Varshney, one use for AI and ML is generating compound hits for a given target, a process that typically screens for molecular structures that can bind to the target from billions of potential molecules. Another use she points out is the prediction of various characteristics of one or more (e.g., 1000s) molecules, including the mechanism of action in the body, toxicity, and more—across different dosing, routes of administration, and formulations. “These predictions can then be used to rank compounds for potential success and failure well before clinical trials, reducing the financial risk associated with developing a drug candidate,” she adds.

AI and ML techniques can also be used to understand how drug candidate efficacy may vary in different patient populations, Varshney continues. These techniques can be used to inform trial design, dosing, and combination therapies, among other things. “Generating predictive patient stratification analysis in this way can improve clinical success and ultimately move us closer to precision medicine care,” she states.

Wishart notes that the industry is seeing a huge interest in applying AI/ML and automation to all steps of the drug discovery process and across all modalities. In target discovery, for instance, huge volumes of data are being linked to select disease-modifying targets. Meanwhile, preclinical and clinical data are being used to select the patient populations for which the drug is beneficial. However, Wishart adds, the area of greatest personal interest is in the early discovery phase (small molecules) where generative models are being used to design compounds optimized in their scoring versus predictive models for parameters of interest, such as on-target potency, early absorption, distribution, metabolism, and excretion (ADME), and selectivity. Using generative and predictive models in this way allows for the ability to better choose compounds for synthesis and testing.

“Success is highly dependent on the predictive utility of such models. As a minimum, models must be able to remove the compounds with the lowest probability of success of meeting the desired profile. Although expectations are typically much higher where we are striving for quantitative predictions of in-vitro data and extending our modeling efforts to pharmacokinetics, efficacy, and safety,” Wishart says.

For example, Charles River, with its partner, Valo Health, created an end-to-end AI-driven approach to drug discovery—in this case small-molecule discovery—called Logica, Wishart says. This approach combines computational AI and experimental approaches to hit identification and optimization. “Ligand-based computational models are used to trawl vast areas of chemical space for potential hit series. If there is no literature data to develop the computational models for the target, then Logica simply leverages experimental high throughput screening (HTS) and DNA Encoded Library (DEL) screening to generate that initial data and to fuel hit finding and model building,” he explains.

In this scenario, hit compounds are optimized to advanceable leads and, ultimately, to clinical candidates through AI/ML-guided approaches to de-risk candidate compounds and ensure that only the best candidates progress. “The Logica concept results in fewer design cycles, fewer compounds synthesized and tested, and enhanced decision-making on progression,” says Wishart.

“The opportunity to integrate the ‘design’ and ‘analyze’ components of the design-make-test-analyze (DMTA) cycle with advances in synthetic route prediction and automation in synthesis seems tantalizingly close,” Wishart continues. He notes that one can envision a near future state where drug discovery experts are driving parts of the drug discovery trajectory through almost closed loop systems comprising AI/ML-enhanced designs and automated synthesis, purification, and testing.

“The DMTA cycle for small-molecule discovery is, of course, a very specific area of drug discovery, and there are also many technology pioneers applying similar principles in the design, optimization, and development of other modalities, including antibodies and peptides,” Wishart states.

In enhancing the early R&D and drug discovery stages, the industry is seeking faster ways to generate, gain insights, and make decisions to get therapies to patients as fast as possible, emphasizes Wishart. One way to gain speed is through the appropriate management of preclinical trials. “The better we manage our preclinical data within organizations and across organizations, the higher probability we will have to make this [speed-to-patient] happen,” Wishart says. “By designing digital systems that simplify the collection, organization, visualization, and sharing of [these] data, we contribute to the progress toward smarter drug discovery. This starts with strong digital architecture, data standards, and connectivity of tool sets.”

It helps that, today, various organizations are working together to join the pieces together and leverage the advances in these tool sets, including AI, ML, and automation. “We see ourselves as a key player in the ecosystem of these technologies,” Wishart states.

“Hybrid AI and model-informed predictions of drug behavior inform the design of preclinical testing to be both prescriptive of testing and orthogonally confirming of testing,” adds Varshney. For example, she explains, AI-based predictions can guide which rat experiments to conduct and how to conduct them; in addition, they can also explain discrepancies and variabilities of observations, which can elucidate important disease pathways.

“Smart drug development is all about accelerating therapies to patients while reducing unnecessary research and development,” Varshney says. To that end, introducing techniques such as predictive analytics early in drug candidate discovery can eliminate dead-end compounds much more quickly. Narrowing the field with such techniques, before performing animal model tests that often result in false positives, can save millions of dollars in testing and assays, she asserts. Meanwhile, closing the early “translational gap” can increase the number of successful drug candidates entering clinical trials.

“Drug discovery is extremely difficult and is often a high-risk, high-reward industry,” Wishart states. “Costs for drug development are high, timelines are lengthy and are accompanied by high failure rates throughout the process. Therefore, elevating the probability of success through means of enhanced knowledge, technology, and automation is of the utmost importance,” he says.

While it is known that the most costly and lengthy phases of drug development are in the clinical phases, the actions taken in the early discovery phase can and will have a significant impact, Wishart stresses. Selecting the right target with the greatest certainty in modulating the disease in humans is imperative, and reducing timelines in the hit-finding and optimization phases can result in benefits to the patient (e.g., faster delivery of the therapeutic) and to the organization (e.g., additional patent life).

There is also potential for de-risking pre-clinical candidates during the optimization phases through the development of advanced safety and pharmacokinetics prediction models, Wishart adds. “Taken together, it is clear that ‘smarter’ drug discovery in the early stages can have a major impact on the downstream success, with the ultimate goal being to develop medicines for unmet medical needs and to get these medicines to patients as quickly and as safely as possible,” he says.

Among the misconceptions that persist around the “smart” technology evolution is the assertion that AI is unreliable. Varshney observes that many scientists believe AI and ML technology can never replace traditional scientific methods, and, therefore, these technologies cannot be trusted to provide value in drug discovery and development. “Much of this mistrust is due to the need for explainability found with many systems. But explainability is now being addressed by many algorithms and within individual technology platforms,” she explains.

For example, Varshney points to a hybrid AI technology utilized by VeriSIM Life (the company’s Translational Index technology), which scores the potential of a compound to succeed in the clinic. The technology also provides an itemized breakdown of the score’s components, which gives insights on what is working, what needs improvement, and recommendations on how things can be done differently for better outcomes. Insights generated may include weighted measures of parameters such as the drug’s properties, animal study outcomes, and first-in-human doses.

Meanwhile, Wishart notes that there are several points to consider around the use of these tools and technologies. For one, there is unlikely to be a magic “smart” solution to drug discovery that will elegantly transform drug discovery into a simple process. Drug discovery is much more complex than that and, as the industry has seen in the past, there will continue to be evolution and progress in the way new drugs are discovered and developed in the future. This evolution will largely be due to the emergence of new and exciting technologies.

“Perhaps the biggest challenges are twofold,” Wishart expounds. “First of all, managing our own expectations, both positive and negative, to truly understand where new developments will have the biggest impact. Secondly, understanding what needs to change to enable that impact—this can encompass co-technologies or deeper cultural changes necessary to embed such developments.” For instance, looking at the role of AI/ML in early drug discovery rather than simply using those tools to bolster current workflows can create competing workflows with traditional tried and tested approaches. This conflict can potentially lead to a challenging environment where the impact of the AI/ML approaches are thus not realized, Wishart cautions.

When referring to this article, please cite it as Mirasol, F. Using Smart Tools for Smart Development. 

The use of smart tools in early drug discovery can have an impact on downstream phases of drug development.

Using Smart Tools for Smart Development

Brian Huber is vice-president of Therapeutic Areas, Drug Development, and Consulting at ICON.

Tamie Joeckel is global business lead of the Cell and Gene Therapy Group at ICON.

Since the first FDA approval in 2017, chimeric antigen receptor T-cell (CAR-T) therapy has garnered excitement as a potentially curative option for hard-to-treat blood cancers (1). In this therapy, T cells are genetically engineered to recognize specific tumor-surface antigens. When the engineered T cells encounter the target antigen, they proliferate and coordinate an immune response to destroy the cells expressing that antigen. There are six approved CAR-T therapies in the United States that target blood cancers. These “autologous” treatments are manufactured from T cells obtained from the patient and are genetically engineered to express a CAR that recognizes an antigen specific to the patient’s blood cancer.

When CAR-T therapy works well, it puts patients with malignant, lethal blood cancers into long-term remission. However, approved CAR-T therapies remain ineffective for many patients, and no CAR-T therapies have been successfully developed for solid tumors (2). The high cost, clinical complexity, and dangerous side effects of existing CAR-T therapies have further limited the application of an otherwise exciting and novel treatment.

Significant obstacles remain before CAR-T therapies can be adopted to treat solid tumors. Persistent efforts to expand CAR-T therapies to solid tumors are focused on identifying solid tumor-specific antigens for CAR T to target, enabling the therapy to penetrate solid tumors and ensuring that the therapy persists and functions in the immunosuppressive microenvironment of the solid tumor.

Because the immune system uses antigens to identify targets, antigens are a key factor in the development of CAR-T cell therapies. To minimize off-target effects, an appropriate antigen target for a CAR-T therapy must be present on cancer cells but not significantly on healthy cells. If a patient receives CAR-T therapy that targets an antigen present on both tumor cells and healthy tissue, the subsequent immune response may attack normal cells and has the potential to generate difficult-to-manage serious side effects.

All FDA-approved CAR-T therapies target either CD19 or B-cell maturation antigen, which are antigens associated with cell development that are highly expressed on blood cancer cells but are only limitedly expressed on healthy cells. While CAR-T therapy for blood cancers has a few clear antigen targets, identifying antigen targets for solid tumors has proved much more complicated.

Solid tumors have a wider array of potential targets than blood cancers, and the antigens expressed on solid tumors are often also found at low levels on normal cells. The overlap in antigen expression between tumor cells and healthy tissue has led to severe toxicity in early solid-tumor CAR-T therapy clinical trials, despite promising results in earlier animal models. Along with the judicious selection of antigen targets, an important parameter for the clinical success of CAR-T therapy will be the development of animal models that better represent the human immune system and the differential expression of the target antigen.

The challenge of selecting a target antigen is compounded by the heterogeneity of antigen expression in solid tumors. This heterogeneity is likely one important reason for the diminished initial and durable CAR T response (3). Heterogeneous expression means that some tumor cells may express an antigen more strongly than others, and some may not express that antigen at all. A CAR-T therapy targeting a cancer-specific antigen that was heterogeneously expressed would miss tumor cells not expressing that antigen and would be less effective on cells weakly expressing that target.

One proposed approach to circumvent the lack of cancer-specific, consistently expressed antigens on solid tumors is engineering CAR T that can identify multiple targets. This could be achieved by genetically engineering multiple CARs into the same T cell or engineering a receptor that would recognize more than one target antigen. However, multi-target CAR Ts can carry an elevated risk of severe side effects from off-target effects (4).

Individual antigens for targeting solid tumors are also under investigation. Cancers sometimes express embryonic genes, such as CLDN6, which are silenced after birth (5). CLDN6, which enables cancers to metastasize, is present in most testicular cancers, as well as in some ovarian, non-small cell lung, gastric, breast, and endometrial cancers. Still, targeting CLDN6 carries some danger of off-target effects, as the protein is expressed at low levels in the pancreas and liver, and a protein with a similar structure, CLDN9, is expressed throughout the body.

A 2022 Phase I/IIa trial of CLDN6-directed CAR-T therapy, called BNT211-01, displayed one of the first examples of CAR T efficacy in solid tumors (6). Initial trial results reported tumor shrinkage in 33% of 21 patients with seven different tumor types, including one testicular cancer patient who went into complete remission. Two additional solid-tumor targets have also shown preliminary promise in clinical trials: a study treating glioblastoma with interleukin 13 receptor subunit alpha 2 (IL13Ra2)-directed CAR-T cells and CAR-T cells targeting prostate stem cell antigen for prostate cancer (7,8).

To attack solid tumors, CAR-T cells must first migrate from blood vessels to the tumor tissue. Then, they must be able to infiltrate and proliferate in the tumor microenvironment. This cell movement is challenging for a number of reasons. For instance, physical barriers, including the extracellular matrix and the vasculature surrounding a solid tumor, make it difficult for CAR-T therapies to penetrate the tumor. Once CAR-T cells penetrate the tumor, the therapy must overcome an immunosuppressive tumor microenvironment that impairs its function and efficacy.

Many strategies for migrating to and functioning within the solid tumor microenvironment are in development, and many more have been proposed. Several of these strategies aim to augment CAR-T function by arming CAR-T cells with additional molecules or combining them with an additional therapy.

For example, boosting expression of some cytokines could make it easier for CAR-T cells to infiltrate solid tumors (9). Cytokines—small proteins secreted by certain immune cells—can enhance tumor-destroying activities of other immune cells, including T cells. “Armored” CAR-T cells, engineered with specific cytokine receptors or engineered to express stimulatory cytokines, have the potential to improve CAR-T therapy’s efficacy (10).

Other proposed strategies for enhancing CAR-T function include engineering CAR-T cells to be insensitive to immunosuppressive conditions and combining CAR-T therapy with immune checkpoint inhibitors (2). However, many of these approaches raise the risk of cytokine release syndrome, a toxic and potentially lethal side effect of CAR-T therapy resulting from excessive inflammatory cytokines in the circulatory system.

One combination therapy approach that has already demonstrated promise in early clinical trials is a messenger RNA (mRNA) vaccine that enhances the proliferation of CAR-T cells. The mRNA vaccine leads to target antigen expression on T-cell-activating immune cells (i.e., antigen-presenting cells). The resulting cell proliferation helps the therapy persist in the immunosuppressive solid-tumor environment and allows the therapy to be administered at lower initial doses. The clinical trial investigating CLDN6-directed CAR-T therapy, mentioned previously, used this strategy in a subset of patients (6). In the preliminary study, 43% of patients treated with a combination mRNA vaccine and CAR-T therapy experienced tumor shrinkage. Still, the efficacy and safety of this method need to be tested and validated in additional trials—approximately 40% of patients treated in the CLDN6 study developed manageable cytokine release syndrome.

Many of the challenges facing CAR-T therapy for solid tumors remain unresolved. However, if history is a guide, these obstacles are not insurmountable. Blood cancers are often selected for development of novel therapies because tumor cells circulating in the blood are easier to access than tumor cells in tissue, and treatments are easier to deliver. Treatment options, such as chemotherapy and stem-cell transplant, were first developed for blood-based cancers and then were modified to treat solid tumors. A number of recent advancements—including the identification of solid-tumor-specific antigens, the development of armored CAR-T cells, and mRNA combination therapies—are bringing this targeted immunotherapy for solid tumors closer to reality.

1. Mullard, A. FDA approves first CAR T therapy. 

 (10), 669–669. DOI:10.1038/nrd.2017.196
2. Marofi, F.; Achmad, H.; Bokov, D.; et al. Hurdles to Breakthrough in CAR T Cell Therapy of Solid Tumors. 

 (1),140. DOI:10.1186/s13287-022-02819-x
3. Chen, N.; Li, X.; Chintala, N. K.; Tano, Z. E.; Adusumilli, P. S. Driving CARs on the Uneven Road of Antigen Heterogeneity in Solid Tumors. 

, 103–110. DOI:10.1016/j.coi.2018.03.002
4. Kailayangiri, S.; Altvater, B.; Wiebel, M.; Jamitzky, S.; Rossig, C. Overcoming Heterogeneity of Antigen Expression for Effective CAR T Cell Targeting of Cancers. 

 (5), 1075. DOI:10.3390/cancers12051075
5. Du, H.; Yang, X.; Fan, J.; Du, X. Claudin 6: Therapeutic Prospects for Tumours, and Mechanisms of Expression and Regulation. 

 (3), 677. DOI:10.3892/mmr.2021.12316
6. Mackensen, A. BNT211-01: A Phase I Trial to Evaluate Safety and Efficacy of CLDN6 CAR T Cells and CLDN6-Encoding mRNA Vaccine-Mediated In-Vivo Expansion in Patients with CLDN6-Positive Advanced Solid Tumours. Presentation at the 2022 ESMO Congress, Paris, France, Sept. 9–13, 2022.
7. Society for Neuro-Oncology, Session 3: Immunotherapy: Hype and Hope. Presentation at the First Annual Conference on CNS Clinical Trials, 

, Oct. 1–2, 2021.
8. Mustang Bio, Mustang Bio Announces Initial Phase 1 Data on MB-105 for Patients with PSCA-positive Castration Resistant Prostate Cancer. Press Release, Oct. 26, 2020.
9. Mollica Poeta, V.; Massara, M.; Capucetti, A.; Bonecchi, R. Chemokines and Chemokine Receptors: New Targets for Cancer Immunotherapy. Front Immunol. 

. DOI: 10.3389/fimmu.2019.00379
10. Hawkins, E. R.; D’Souza, R. R.; Klampatsa, A. Armored CAR T-Cells: The Next Chapter in T-Cell Cancer Immunotherapy. 

Brian Huber is vice-president of Therapeutic Areas, Drug Development, and Consulting, and Tamie Joeckel is global business lead of the Cell and Gene Therapy Group; both at ICON.


Vol. 47, No. 5
May 2023
Page: 26–27,31

When referring to this article, please cite it as Huber, B.; Joeckel, T. Challenges of Expanding CAR-T Cell Therapy into Solid Tumors. 

The development of CAR-T therapies for solid tumor cancers presents a myriad of challenges.

Challenges of Expanding CAR-T Cell Therapy into Solid Tumors

Cheryl Barton is director of PharmaVision, 

For several years, manufacturers have been developing organs‑on‑a-chip (OoC) technology, whereby engineered or natural tissues are grown inside microfluidic chips allowing them to maintain tissue-specific functions. Today, OoCs encompass an array of tissues and organ functionality including the blood-brain-barrier (BBB), central nervous system (CNS), heart, intestine, liver, lung, kidney, muscle, and skin to allow pharma to better understand the underlying pathophysiology of diseases and to determine the effect of drugs 

Advances in tissue engineering, microfabrication, and biocompatible microfluidic chambers alongside the governmental (2) and regulatory (3) appetite to seek animal-free innovations in the drug development process has fuelled further interest and investment in this marketplace. According to market research, the global OoC market is forecast to be worth US$388 million (€354 million) by 2028 increasing from US$82 million (€75 million) in 2023, with a compound average growth of 36.4% from 2023 to 2028 (4).

Market leaders carving out a niche in the OoC market

Several players have already carved out niches in the OoC field. CN Bio Innovations, a spin-out from Oxford University in the United Kingdom, was founded in 2008 and became one of the first companies in this space with OoC technology licensed from Massachusetts Institute of Technology and Vanderbilt University. CN Bio has developed a range of single OoC technologies including the gut, liver, or lung, and recently launched the PhysioMimix platform, a system that can co-culture human cells (e.g., gut/liver) in open-well plates to recreate human organs. Importantly, multiple devices can be connected together to generate a ‘body-on-a-chip’ device whereby microchannels allow different organs to interact with one another (5).

Another player in the field of OoC, TissUse, was founded in 2010 and is a spin-off from Technische Universität Berlin. The biotech company produces models of human organs for preclinical drug testing based on this patented technology. Like CN Bio, TissUse has developed a multi-organ system or human-on-a-chip technology to allow potential interaction of one organ with another. This technology has been used in drug development, consumer products, cosmetics, and food and nutrition products to help predict absorption, distribution, metabolism, and excretion (ADME) and toxicity (6).

Netherlands-based Mimetas was founded in 2013 and has raised more than US$25.2 million (€23 million) in series A and B funding (7). In March 2022, it launched a three-dimensional (3D) OrganReady Coco-2 assay consisting of 38 intestinal tubules that facilitate the pre-clinical assessment of ADME, safety, and toxicology of new chemical entities (NCEs) and later the same year won the Dutch Innovation Award in recognition for its innovative technology (8). In July 2021, it entered into a strategic partnership with Roche to develop 

 models of inflammatory bowel diseases and hepatitis B viral infections, which it successfully completed in March 2023. Mimetas has also teamed up with Astellas Pharma to utilize its Organoplates for high throughput (HT) 

 screening of Astellas’ next-generation immune-oncological therapies (9). Mimetas continues to push the frontiers of OoC and recently launched its off-the-shelf solution, OrganoReady consisting of 3D Adult Stem Cell (ACS)-derived tubular organoid assay derived from either the colon or kidney for use in preclinical research (10).

In the United States, microfluidic start-up Emulate was established in 2014 and became one of the first companies to develop the Liver-Chip for predictive toxicology (11); the technology was developed at the Wyss Institute for Biological Inspired Engineering at Harvard. Like other OoC companies, Emulate is now researching personalized medicines through a human-on-a-chip approach. New York-based TARA BioSystems was also created in 2014, a spin out from Columbia University and became one of the market leaders in heart-on-a-chip technology. It was recently acquired by Valo Health in April 2022, enabling it to expand its cardiac disease modelling capabilities (12). Meanwhile, Florida-based Hesperos a global contract research organization (CRO) has ventured into the OoC space and now offers clients inhouse safety and efficacy testing services. It has developed a multi-organ 

 platform, ‘human-on-a-chip’ technology, to allow drug developers to investigate patients’ response to drugs during pre-clinical and clinical development. Hesperos has forged collaborations with Roche and Sanofi to pre-clinically evaluate NCEs for ADME and toxicity; these data have been used to support investigational new drugs (IND) files (13,14).

Newcomers in the OoC field attracting investor attention

As the field of OoC moves forward at a pace, several European start-ups have recently entered the arena and gained investor attention.

In March 2022, Lyon-based NETRI, attracted €8 million series A funding to help develop its novel high throughput (HT) compartmentalized microfluidic brain-on-a-chip and skin-on-a-chip technology for use by the pharma and cosmetic industry (15). The NeoBento HT 96-well plate contains between 16 and 24 chips that are interconnected by microchannels (e.g., tunnels or grooves) allowing cells to be co-cultured and recreate physiological interactions. Unlike other OoC technologies, the microchannel grooves allow continuous connection between compartments allowing research to study axotomy, the gut brain axis, the neuromuscular junction, and innervated skin and evaluate therapeutic agents for neurological conditions such as multiple sclerosis and neuropathies. NETRI’s microfluidic chips can also be used to mimic physiological barriers such as cell membranes to allow companies to assess how substances are transported across the cell membrane including the blood brain barrier.

In September 2022, NETRI teamed up with Axion Biosystem to develop a HT microchip that is compatible with multielectrode arrays (MEA) (16). In March 2023, the companies launched the NeoBento MEA a HT 96-well plate that enables electrophysiological recording of cells 

; this allows pharma to remotely stimulate the cell and monitor synaptic activation in isolated cell populations (17). The technology is currently designed for use in peripheral nerve injury (peripheral neuropathic pain and allodynia, nociceptive pain) and sensitive skin syndrome as well as the evaluation of neurodegenerative diseases (Alzheimer’s disease, Parkinson’s disease) and other neurological disorders. NETRI has adopted a modular approach that allows the OoCs to be combined to create multi‑organ or multi‑organoid formats and these can be customized to clients’ requirements, enabling them to rapidly and cost‑effectively screen NCEs and select the most appropriate drugs to move forward into clinical development (

NETRI high throughput organs-on-chip platform, NeoBento, for drug discovery and cosmetic testing. 

In March 2022, Netherlands-based Bi/ond, secured US$4 million (€3.6 million) investment from leading industrial venture firm FORWARD.one to develop its proprietary inCHIPit and the reusable comPLATE platforms that combine 3D microfluidic cell culture within a microchip for applications in kidney research, oncology, and cardiac simulation (19). The inCHIPit is an open well system that can be loaded with a variety of cells or tissues (e.g., pluripotent stem cells, organoids, 

 tissues, spheroid, or microtissues) and each well is connected to microfluidic channel via a porous membrane, which allows cells to be stimulated 

 and viewed optically. Bi/ond is currently evaluating its technology to predict treatment response and personalize therapy. For instance, the company has forged a collaboration with the Leiden University Medical Centre (Netherlands) to culture heart OoCs so that patients’ response to therapy can be predicted, and the company is working with the Erasmus University Medical Center (Netherlands) to generate OoCs containing patient tumour tissues to assess their response to chemotherapy (19).

As OoC manufacturers continue to embrace the adoption of new biomaterials and fabrication techniques such as lithography and 3D bioprinting this will allow companies to increasingly customize multi-OoC systems with the desired functionality and will provide high content imaging and/or electrophysiological readouts (1). To date, the use of OoCs has primarily focused on drug development; however, they also offered considerable potential throughout preclinical and clinical development, providing new ways to model diseases, including rare disorders, monitor pharmacokinetic and pharmacodynamic properties of NCEs, and guide the personalization of treatment in the clinic based on genotypic-phenotypic characteristics. Given the recent regulatory move to reduce animal testing (3) the field of OoC looks ripe for innovation and further investment.

1. Leung, C.M.; de Haan, P.; Ronaldson-Bouchard, K.; et al. A Guide to the Organ-on-a-Chip. 

, 2, 33.
2. European Commission. JRC Supporting Alternatives to Animal Testing. 

, News Release, 7 April 2022.
3. Wadman, M. FDA No Longer Needs to Require Animal Tests Before Human Drug Trials. 

, Article, 10 Jan. 2023.
4. Market Data Forecasts. 

Global Organ-on-Chip Market Size, Share, Trends, COVID-19 Impact and Growth Analysis Report—Segmented by Type (Heart-on-chip, Human-on-chip, Intestine-on-chip, Kidney-on-chip, Liver-on-chip and Lung-on-chip), Application and Region (North America, Europe, Asia-Pacific, Latin America, Middle East and Africa)—Industry Forecast from 2023 to 2028

. Market Report, March 2023.
5. CN-Bio. PhysioMimix OOC Microphysiological Systems. 

, accessed 3 April 2023.
6. TissUse. Technology. 

, accessed March 2023.
7. Mimetas. MIMETAS Secures 20 Million Dollar Series B Financing. 

, Press Release, 11 April 2018.
8. Mimetas. MIMETAS Elected Most Innovative Company of the Netherlands. 

, Press Release, 2 Nov. 2022.
9. Mimetas. MIMETAS and Astellas Enter into Strategic Partnership on Immuno-Oncology. 

, Press Release, 28 March 2023.
10. Mimetas. MIMETAS Launches Ready-to-Use 3D Adult Stem Cell Organoid Tubules. 

, Press Release, 7 March 2023.
11. Ewart, L.; Apostolou, A.; Briggs, S.A.; et al. Performance Assessment and Economic Analysis of a Human Liver-Chip for Predictive Toxicology. 

, 2, 154.
12. Valo. Valo Health Acquires TARA Biosystems Creating First of its Kind Vertically Integrated Cardiovascular Platform. 

, Press Release, 5 April 2023.
13. Hesperos. Hesperos Shows Potential for 

 Approach to Replace Conventional Animal Efficacy Studies for Rare Neuromuscular Disorders. 

, Press Release, 19 April 2022.
14. Hesperos. The Original Human-on-a-Chip Company. 

, accessed 3 April 2023.
15. NETRI. Lyon-Based Industrial Start-Up NETRI is Finalizing an €8 million Series A Funding Round. 

, Press Release, 3 Mar. 2022.
16. NETRI. NETRI and Axion BioSystems Announce Organs-on-Chip Collaboration. 

, Press Release, 8 Sep. 2022.
17. Business Weekly. Axol Bioscience and French Partner Unveil Organs-on-Chip Innovation. News Release, 3 Jan. 2023.
18. NETRI. Modular Integration. 

, accessed 3 April 2023.
19. Bi/ond. Bi/ond Secures Over $4M in Funding—Bi/ond. 

Competition in the organ-on-a-chip market increases as NETRI enters the arena.

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