Agnes Shanley is senior editor of Pharmaceutical Technology.

Agnes Shanley

	Under US regulations, such as the Medicare Access and CHP Reauthorization Act of 2015 (MACRA), part of any US physician’s reimbursement will be based on patient outcomes. Similarly, value-based contracts will reward manufacturers for drugs that improve patient outcome, and penalize them for treatments that don’t show clear results. Insurers have moved to value-based contracts in hepatitis C and oncology drugs and are moving it to multiple sclerosis and rheumatoid arthritis, according to a recent study (1), Since 2015, Novartis, Lilly, Gilead, Amgen, Sanofi and Regeneron have set up such contracts for specific therapies (2-4).

	This approach increases risk, because physicians and drug companies have little control over patient behavior. The key is developing methods that trick people into making the right decisions, says Dr. Bertalan Mesko, The Medical Futurist, a physician and blogger. He notes the health insurance company, Oscar, which offers its subscribers health trackers and gives gift cards to those who walk more than 10,000 steps per day. Currently, he says, a small number of people in the US use most of the nation’s healthcare services. Some insurers are considering strongarm tactics, such as dramatic increases in premiums, for patients who choose to live unhealthy lifestyles.

Health Plans ae Interesting in Tying Drug Prices to Patient Outcomes

,” Press Release, avalere.com, June 16, 2016, accessed April 7, 2017. 
	2. “

Cigna Implements Value-Based Contract With Novartis for Heart Drug

,” News Release, cigna.com.
	3. S. Barlas, “

Health Plans and Drug Companies Dip Their Toes into Value-Based Pricing

,” nih.gov, Pharmacy and Therapeutics, January 2016 41(1); 39,40, 41, 52.
	4. T. Staton, “

Most US Payers are Eyeing Outcomes-Based Drug Pricing Report

	When referring to this article, please cite it as A. Shanley, “MACRA and Value-Based Contracts” sidebar to “Innovating in a Value-Based World," 

Articles

Under US regulations, such as the Medicare Access and CHP Reauthorization Act of 2015 (MACRA), part of any US physician’s reimbursement will be based on patient outcomes. 

MACRA and Value-Based Contracts

As the $3.4-trillion US healthcare industry adopts value-based practices to help control runaway costs and address imbalances in access, physicians and pharmaceutical companies find themselves in a similar situation: their performance will be judged, and payment based, on how well patients respond to their care or their products (see Sidebar).

	This responsibility may frighten some doctors and pharmaceutical company executives, especially given the number of patients who refuse to comply with orders or take their medicine. Noncompliance accounts for $290 billion in medical costs each year, according to the New England Healthcare Institute (1).

	Others, however, see the new focus on results as a way to reach out to or even retrain patients, reduce waste and costs, and regain the public’s trust. “We want to be rewarded for the tangible outcomes that our products provide patients, not for simply selling pills,” wrote Novartis CEO Joe Jimenez in a November 2016 editorial in 
	

	Jimenez then went on to define any drug or treatment’s value based on the following metrics:

		Improved survival rates (e.g., for oncology treatments)

		Improved overall patient response (e.g., in clinical trials)

		Better patient experience (e.g., reduced side effects and improved quality of life)

		Impact on overall healthcare (e.g., whether it reduces the need for doctor’s office visits)

		Value to society (e.g., reducing the economic impact of lost workdays, etc.).

	Just as hospitals are moving away from individual to “bundled” services, pharmaceuticals will no longer be viewed as discrete products, but integrated treatment packages. Many of these will look like ordinary pills, capsules, or vials, but their formulations may incorporate precision medicine features (e.g., be designed for a specific patient population) and they are sure to be sold with one or all of the following: a smart phone app, companion monitoring and/or dosing device, or sensor.

	In other cases, tomorrow’s pharmaceuticals won’t even be recognizable dosage forms, but combination treatments that could involve devices designed to generate electrical impulses or optical waves. An increasing number of them are likely to be therapies derived from the patient’s own cells.

	More manufacturers are starting to design these products to help ensure, first, that patients take the treatment, but, second, to communicate with patients and help them manage dosages, remain engaged with healthcare providers, or stay in clinical trials.

	Eventually, drug manufacturers will need to go farther. “Pharma must shift its focus from treating diseases to preventing them,” says Dr. Bertalan Mesko, the Medical Futurist, a physician who envisions the impact of digital technology on the future of healthcare. “Pharmaceutical companies will need to change their whole approach to the business,” he says.

	The biggest change that pharmaceutical companies are grappling with is the fact that physicians and patients are becoming equal partners in treatment. “There is no hierarchy anymore,” says Mesko. “Digital health means that data should be available to physicians and patients at the same time and that both are in an equal partnership.”

	Today, it’s easy to find patients (or their parents or family members) running patient action groups, corporations or foundations dedicated to rare diseases. Empowered by access to information and, via social media, introduced to others facing the same issues and experts treating or developing cures, patients will no longer tolerate physicians dictating treatment regimens from on high.

	Similarly, pharma companies can’t simply sell them a bottle of pills and leave it at that. “Patients want to take an active part, not only in their own treatment but in helping companies produce better drugs for them,” says Mesko. “Producing drugs is just not enough anymore. How effectively pharmaceutical manufacturers respond to this change will determine whether they can even survive, says Mesko (3).

	A real concern, he says, is that, in the future, more patients may start up health-tech ventures or turn to tech-based treatments including apps, monitoring and dosing devices, virtual reality, and 3-D printing on their own, bypassing pharma, regulators, and even healthcare providers.

	As he points out, this has already happened in the past, when some parents of children with Type 1 diabetes put together their own, unregulated monitoring and dosing devices to handle challenging dosing issues that device and drug manufacturers were not addressing rapidly enough (4). “Even though we want patients to be equal partners in the decisionmaking process, we do not want them to bypass the regulatory process and try to help solve their medical issues themselves, with startups in their garages.  We want to help push FDA forward for companies that are working on innovations,” says Mesko.

	For the past few years, manufacturers have begun to focus on engaging patients and making it easier for them to comply with physicians’ prescription orders for any new drug (e.g., via more convenient dosing or delivery). This focus is reflected, for example, in formulations such as controlled release and orally disintegrating tablets, improved autoinjector systems and inhalers, as well as biopharmaceutical formulations that don’t require infusion or that can be taken less frequently.

	Companion diagnostics are also being developed for more pharmaceuticals. In 2006, there were only five drug-companion diagnostic combinations on the market, but by 2012 the number had grown to 63 (5). Roche continues to work on drug and companion diagnostics packages, and 60% of its target drug candidates are being developed with a companion device (6).

	But devices are also going beyond simply measuring the level of a marker in the body to dynamic real-time measurement, dosing, and control. Research is progressing in disease areas that are difficult to dose correctly, especially in children, notably asthma and Type 1 diabetes.  In the United Kingdom, clinical trials are currently underway evaluating a Bluetooth-enabled smart inhaler that would allow healthcare givers to observe patient’s dosage and technique (7).

	In 2016, FDA approved Medtronic’s first “bionic pancreas” for diabetes (8), designed to measure blood levels of glucose continuously, then control delivery of insulin when levels get too high or too low. Too much insulin can lead to hypoglycemia, which can result in patient death, especially at night.

	In advanced clinical trials is BetaBionic’s i-Let, named for part of the organ whose function it mimics, another bionic pancreas (9) developed by the father of a boy with Type 1 diabetes. It uses advanced algorithms and sensors to monitor glucose levels and administer insulin when glucose levels get too high and glucagon, which was recently processed in a more stable form by Xeris Pharmaceuticals (10), when they get too low.

	Mobile health apps, whether developed in house or with outside partners, have become a given at most large pharma companies today, to engage patients and healthcare providers and promote the communication that can be so crucial to optimizing patient outcomes. Sanofi, Johnson & Johnson (J&J), Merck, and GlaxoSmithKline (GSK) have developed the best known apps. Approaching this from the tech side are companies such as Monsenso, which offers apps to help patients deal with mental disorders ranging from bipolar to schizophrenia.

	GSK, Boheringer Ingelheim, and Novartis are working with another m-health provider, Propeller, which is developing a smart inhaler via an add-on and a smart phone app that would help patients treat asthma (11).

	But some tech companies have also been developing apps that might compete with pharmaceutical treatments. They might not, on their own, be useful in treating cancer or diabetes, but could ameliorate symptoms of some mental conditions such as anxiety, or help patients deal with “lifestyle” conditions, e.g.,  Sleepio, Big Health’s digital treatment for insomnia (12). In the UK, government agencies, and even the National Institute for Health and Care Excellence, have started to track and rank m-health apps (13, 14).

	Tech companies are also developing augmented and virtual reality to help treat conditions ranging from post-traumatic stress disorder (15) to agoraphobia and schizophrenia (16). Pharma companies are working with virtual reality in the diabetes area with NovoNordisk’s Diabetes Voyager, which uses Samsung’s Oculus Rift technology and the xBox to simulate what diabetes is and what it does (17). Other companies have developed virtual reality tools to give caregivers and healthcare providers an idea of what patients go through. Examples are J&J’s Virtual Hallucination (18), which simulates the schizophrenic’s experience, and Merck’s MS Inside Out (19), recently completed with Studio Lidell, which offers interactive insights into multiple sclerosis. An example of augmented reality is AstraZeneca’s Fit2Me digital coach for diabetes (20).

	If patient communication is crucial in a value-based environment, so is reducing the cost and timelines for clinical trials and drug development. Pharmaceutical manufacturers are collaborating with universities and research companies to leverage advances in science and technology that will allow them to filter through noise and solve problems much faster and more efficiently.

	The single most important tool now available is artificial intelligence (AI), and powerful algorithms that allow patterns to emerge from huge volumes of data.  “AI can allow a company to do a year’s worth of research in a day,” says Mesko. “The results could take drug development to a whole new dimension,” he says.

	More pharma companies are collaborating with AI specialists, who, in turn, have added simulation and the techniques of precision medicine to their toolkits. Merck, for example, is working with Atomwise, which uses in-silico models and deep learning algorithms to find new combinations of drugs that could treat existing disorders, or find new drugs from huge databases (21). The company did this recently, to find a treatment for Ebola.

	Turbine is another research firm that uses simulation and artificial intelligence to help companies repurpose drugs and drug combinations and focus on likely candidates, using models to run millions of virtual trials on simulated cancer cells. The company plans to make personalized cures possible for every cancer patient by the next decade (22).

	Pharma companies are also evaluating AI as a way to improve clinical research. One goal is targeting the best candidates for clinical trials so that testing is no longer random but focused on the patient groups that could potentially benefit most from the treatment. Oncompass, which focuses on the specific cancer tissues and types unique to each patient, sequences the DNA of tumor cells and then runs results through a database to determine the most relevant trials for patients with that type of tumor (23).

	In-silico clinical trials, combining AI with simulation and modeling, won’t be that far off, Mesko says. “It’s nonsense to take a decade and billions of dollars to test a new drug on human beings, when thousands of people could be tested in days using in-silico methods and a supercomputer (e.g., IBM Watson) and human physiological models.”  In Europe, the Avicenna Support Action has developed a roadmap (24) for in-silico clinical trials in the future.

	New patient-centered clinical trial models are already being seen. Sanofi, for example, is working with Science 37 on a digital clinical trial design for a siteless trial (25) that would use digital technology to communicate with and engage physicians and participants. Science 37 claims that the new approach could reduce the time required by 30% or more, potentially shaving two years off the time required for each trial.

	Genomics has become far more accessible within the past few years, with the cost of genome sequencing moving from hundreds of thousands of dollars to $1000 and getting cheaper. “Now, companies have new tools and a chance to make meaningful therapies,” says Mesko.

	As gene and cell therapies are developed, pharmaceutical companies are also entering into research projects involving gene-editing techniques. One of the most promising techniques is CRISPR, says Mesko, although it poses serious ethical questions, including concerns that there might be attempts to develop “designer zygotes” in the future.

	At this point, it is being evaluated mainly to treat rare, genetically-based diseases. Bayer AG and CRISPR Therapeutics recently launched a venture that would evaluate its use in treating blood diseases and other conditions (26). China was the first to actually inject human patients with CRISPR-edited genes in clinical trials for cancer treatment (27), but in the United States, tests are expected to begin in 2017 to evaluate gene editing in cancer T-cell therapies and as an option for treating a rare form of blindness (28).

	Some of tomorrow’s therapies will look like nothing we’ve seen to date. An example is electroceuticals, which use electricity from a tiny implanted device to change electrical impulses within the body. GSK has invested significantly in the technology (29), and plans to start clinical trials with external partners at some point in 2017 and internally in 2019.

	Farther away from development is optogenetics, which applies light to neurons in the brain, activating or deactivating specific areas (30). Mesko believes that this research will be extremely important in developing treatments for neurological conditions in the future.

	In the end, what will make effective innovation possible is better patient data. For the past few decades, physicians have been required to invest in and use electronic health record systems (EHRs). Patient data will be essential to developing evidence on best treatment practices and responses to specific therapies.

	With value-based care, the pharmaceutical industry and US healthcare are on a highway that is still under construction. AI and advances in sensors, devices, and mobile health offer pharma the opportunity to keep its innovation alive and relevant.

Why the Approach to Drug Pricing Has to Change Now

,” forbes.com, Nov. 1, 2016, accessed April 7, 2017.
	2. New England Healthcare Institute, “

Think Outside the Pillbox: A System-Wide Approach to Improve Patient Medical Adherence for Chronic Disease

,” nehi.net, August 2009, accessed April 7, 2017. 
	3. B. Mesko, 

, accessed April 7, 2017.
	4. D. Hurley, “

Diabetes Patients are Hacking Their Way to a DIY Bionic Pancreas

, wired.com, December 24, 2014, accessed April 7, 2017.
	5. A. Agarwal et al., Pharmagenomics and Personalized Medicine, 2015 (8), 99-110; 
	6. D. Garde, “

,” Sept. 5, 2012, accessed April 7, 2017.
	7. “

Smart Asthma: Real-world implementation of connected devices in the UK

FDA Approves First Automated Insulin Delivery Device for Type 1 Diabetes

,” fda.gov, News Release, Medtronic bionic pancreas approval.
	9. E. Damiano, 

, www.betabionics.org/tedx 
	10 Xeris Pharma website, Pipeline page, stabilized glucagon, accessed April 7, 2017.
	11. B. Hirschler, “Your Inhaler’s Watching You,” uk.reuters.com, July 20, 2016, uk.reuters.com/article/us-health-pharmaceuticals-inhalers-idUKKCN1001KU, accessed April 7, 2017. 
	12. P. Olson, “

This App is Conquering Insomnia and Depression at the Same Time

,” forbes.com, July 27, 2016.  
	13. D. Tyler, 

, pmlive.com, March 14, 2013, accessed April 7, 2017.
	14. R. Clifford, “

NICE to Bring HTA Processes to Mobile Health Apps

,” pmlive.com, February 2, 2017, accessed April 7, 2017.
	15. 

Bravemind: Virtual Reality Exposure Therapy as a treatment for PTSD

Studying and Treating Schizophrenia Using Virtual Reality

,” Schizophrenia Bulletin, 34(4) 2008, pp. 605-610.
	17. 

, Youtube.com, June 21, 2016, accessed April 7, 2017.
	18. P. Tabar, 

, behavioral.net, October 1, 2007, Hallucination, accessed April 7, 2017.
	19. A. Jardine, 

Virtual Reality Helps MS Patients Rediscover Their Passions in Moving Film

, creativityonline.com, accessed April 7, 2017.
	20. AstraZeneca, 

In-Situ Clinical Trials: How computer simulation will transform the biotech industry

,”Avicenna-isct.org.
	25. Sanofi Le Hub, “

Sanofi Launches Digital Clinical Trials to Improve Recruitment and Reduce Trial Times

,” lehub.sanofi.com, Feb. 3, 2017, accessed April 7, 2017.
	26. 

Bayer Forms Gene Editing Venture with CRISPR Therapeutics

, Press Release, reuters.com, Dec. 21, 2015, CRISPR and Bayer, accessed April 7, 2017.
	27. S. Mukherjee, “

China Has Launched the First-Ever CRISPR Gene Editing Trials on Humans

,” fortune.com, Nov. 15, 2016 , accessed April 7, 2017.
	28. S. Reardon, “

First CRISPR Clinical Trial Gets Green Light From US Panel

,” nature.com, June 22, 2016, accessed April 7, 2017.
	29. S. Simon, 

Google Spinoff teams with Pharma Giant to Treat Disease by Zapping Nerves

, statnews.com, August 1, 2016, accessed April 7, 2017.
	30. J. Colapinto, 

, newyorker.com, May 18, 2015, accessed April 7, 2017.

	When referring to this article, please cite it as A. Shanley, “Innovating in a Value-Based World," 

Value-based medicine is putting patients at the center of pharmaceutical R&D and forcing the industry to move from treatment to prevention.


Innovating in a Value-Based World

	In 2016, the pharmaceutical manufacturer Johnson & Johnson Supply Chain (JJSC) and the distributor AmerisourceBergen launched a four-week pilot program to test GS1’s EPCIS standards and to see how effectively data could be transferred between the two partners. JJSC has been working on serialization for some time, and began shipping serialized product back in 2012, so both companies were fully connected, in terms of their IT, and they could try this approach with serialized product. The test simulated the real-world supply chain. 

	A DataMatrix barcode was applied containing a serialized global trade item number (GTIN), batch and lot number, and expiration data for each sellable unit (whether bottle, vial, or blister), and the units were packed into cases and loaded onto pallets, while downstream vision systems and scanners read the barcode to capture all the information. EPCIS recorded events associated with the GTIN, so that AmerisourceBergen could confirm receipt of each item sent by JJSC, automatically. 

	Results showed not only the viability of this approach, but its potential power. “It’s like electronic data interchange (EDI) on steroids,” says Mike Rose, vice-president, supply chain visibility at JJSC. “Over time, supply chain partners will be able to exchange a lot of critical data for additional value,” he says. The pilot ensured that all processes, from plant to warehouse and distribution channel to docks, were tracked. “It forced us to test all processes along with way. We got confirmation from our partner that everything fed back to them, from plant to distribution center, and that they were receiving relevant process data.” Rose expects to see return on investment in terms of improved inventory management and transparency in the future. “But for now, our focus remains on the patient first,” he says. 

In a pilot program, Johnson & Johnson Supply Chain and AmerisourceBergen demonstrated how data can be transferred between two partners.

Putting GS1’s EPCIS Standards to the Test

Cell, tissue, and gene therapies challenge the world’s regulators as few concepts have. There is little precedent for regulating these dynamic, variable systems, which require a radical redefinition of such established terms as “formulations,” “active ingredients,” and “excipients.”

	As FDA has noted (1), GMP issues come into play, not so much with autologous materials, but with allogeneic materials, which must be stored and processed, increasing the potential for contamination. In the United States, current good manufacturing practice (cGMP) regulations, including 

 (CFR) Parts 210, 211, and 1271, are being applied (2). Although guidance documents for excipients and findings from research into vaccines and biopharmaceuticals are being adapted for use with advanced therapies, there are few insights into how processing affects the materials, and what impact it has on efficacy and overall safety.

	Regulatory agencies must find a balance between overly rigid and prescriptive guidance, which could prevent investment into research and promising new treatments, and insufficient requirements, which could leave patients vulnerable to safety problems. In Europe, where only eight advanced therapies are currently licensed (3) (compared with 14 in South Korea [4] and 14 in the US [5]), this conflict between flexibility and inclusivity is playing out in full force. In February 2017, the Pharmaceutical Inspection Co-operation Scheme (PIC/S), a group of national pharmaceutical inspection authorities, complained that the European Commission’s (EC’s) proposed cGMP guidance for advanced therapies was too lax (6). The EC had issued draft guidance in 2015 asking for industry comments, and reissued it in June 2016 (7,8). Its aim was to provide a risk-management framework that would provide flexibility to account for the variability that these therapies present. The EC stood by its decision after receiving the PIC/S letter (9).

	One fundamental area in need of clarification is the potential impact of raw materials that are used to process advanced therapies. A number of different excipients (e.g., buffers and salts, polymers, and preservatives) may be used to stabilize cells, alter their permeability, or improve delivery.  In addition, cells will come into contact with culture media and media degradation products, trace amounts of which may remain in cells after harvesting. As Fouad Atouf, PhD, vice-president of Biologics and Biotechnology, US Pharmacopeial Convention, and colleagues noted in a paper published in 

 in 2016, there is a need for good assays and efficient washing practices, as well as an effective way to account for residuals in toxicity assessments (10).

	Researchers are using established excipients (e.g., water-soluble poloxamer hydrogels) in some advanced therapy development programs. Safety profiles for well-characterized materials can be extrapolated for advanced therapies, Atouf wrote, but the impact of the materials on cells, and cells on materials, must still be studied (10).

	USP has been developing standards, and is working on testing procedures and references, to help manufacturers of advanced therapies manage potential risks posed by ancillary materials. 

 General Chapter <1046> (11) summarizes best practices. Work is also underway to revise Chapter <1043>, “Ancillary Materials for Cell-, Gene- and Tissue Engineered Products,” and USP plans to release the draft for comments this summer (12). Fouad Atouf discussed risk issues, and evolving compendial standards, with 

 What materials pose the greatest potential risk?

 In the highly specialized field of cell therapy, when qualifying ancillary materials, anything that is not an active ingredient would be considered a raw material, including cell culture media and wash solutions, as well as process materials and aids. Unintended materials that may end up in the finished product should be considered as excipients. Information, documentation, and selection criteria for these materials are needed from the very earliest stages of research.

	Some materials may be more critical, or pose greater potential risk to patients, than others. We are comparing upstream vs. downstream in the process. Basically, a material’s use earlier in the process reduces its level of risk. We’re also comparing animal derivatives with synthetic products. Another important consideration is the amount of material involved, whether grams, micrograms, or kilograms.

 <1043> for raw materials specifies the use of pharma-grade materials. In some cases, though, these may not be available, or can be very expensive for researchers to use. In another common scenario, a raw material may be made in a GMP-compliant environment, but intended for a different use. Developers must be sure that they have adequately qualified the material and its supplier. With materials that have already been used in the same application, one can be more confident that they can be safely used.

	Generally, the highest risk is involved with materials that are made by suppliers that sell to multiple industries, since pharmaceuticals may be only a small part of their business.

	In short, ancillary materials used in advanced therapies are not common raw materials with monographs that are made in GMP environments, and there are no compendial documents for these materials. In such cases, guidance from the International Organization for Standardization (ISO) and International Council for Harmonization (ICH) is extremely relevant, as are the principles of pharmaceutical quality by design, in that one must have control over processes and document all incoming materials. We have started to work on tools that will help manufacturers do this, and are ranking different materials based on the potential risk that they might pose to patients.

 When did you start this work, and what materials have you studied most extensively?

 Efforts started around eight years ago with cell culture supplements and fetal bovine serum (FBS). We developed identification, functionality, and a reference standard for FBS and for the enzyme, trypsin.  We hope to do this for media, a crucial raw material, but one that can be made up of 50 or more components. We are in the process of getting information and prioritizing efforts. USP already has compendial standards in place for amino acids, carbohydrates, and vitamins. We need them for these ancillary processing materials, to be able to calibrate their performance.

 By early summer, we hope to begin the characterization of two to three materials. After early characterization, we will then study their performance to develop standards. We invite suppliers to share data, test their materials, and work with us. Our goal is to develop more standards like the ones that we already have for FBS. We plan to produce reference standards and make supporting documentation available.  This work could also be supported by monographs. In some areas, such as media, we may have to work one on one with some suppliers.

FDA Regulation of Stem Cell-Based Therapies

,” nejm.org, October 19, 2006.
	2. F. Atouf et al., “

Standards for Ancillary Material Used in Cell and Tissue Based Therapies

,” BioProcessInternational.com,  Sept. 1, 2013.
	3. T.Cynober, “

Why are There Only Eight Cell...Therapies Approved in Europe?

Cellular Gene Therapy Products, Marketed Products, Vaccine, Blood and Biologic

Regulatory Update on Cell and Gene Therapy Products...

PIC/S Takes Strong Stance on EC’s Proposed Standalone ATMP GMP Guideline

Consultation Document GMP for Advanced Therapy Medicinal Products,

” ec.europa.eu.
	8. European Commission, “

Summary of the Responses to the Targeted Stakeholder Consultation on the Development of GMP for Advanced Therapy Medicinal Products

EC Says Separate GMP for Cell and Gene Therapies is Necessary

,” in-pharmatechnologist.com, March 21, 2017.
	10. F. Atouf et al., AAPS Journal, 18 (4), July 2016.
	11. S. Seaver, 

, Volume 2, Issue 1, January 2000, Pages 45-49 sciencedirect.com.
	12. USP, <1043> Proposed General Chapter Revisions, 

Ancillary Materials for Cell, Gene and Tissue Engineered Products

	When referring to this article, please cite it as A. Shanley, “Redefining Excipients for Advanced Therapies," 

As regulators strive for balance in cGMPs for cell, gene, and tissue therapies, risk-management principles must guide decisions involving process media and additives.

Redefining Excipients for Advanced Therapies

Continuous manufacturing has been around since the 18th century and is the mainstay of metal manufacturing, petrochemicals, food processing, and other process industries. For decades, some pharmaceutical processes, such as roller compaction, have been operated semi-continuously (1).

	Within the past 10 years, however, through efforts that include work at leading universities; the Novartis/MIT Institute and its spinoff, Continuus Pharmaceuticals; and support from FDA and other regulatory agencies, continuous pharmaceutical manufacturing has begun to get more serious attention as a way to lower drug manufacturing costs and increase efficiencies. A turning point appeared to be reached in 2015, when FDA approved Vertex Pharmaceutical’s cystic fibrosis treatment, Orkambi (2), the first API manufactured via continuous processing.

	In December 2015, FDA invited industry to comment on its first draft guidance document aiming to establish a modern manufacturing infrastructure, including continuous processing (3).  In 2016, FDA approved Janssen Pharmaceuticals’ switch from batch to continuous processing for manufacturing the HIV treatment, Prezista (4,5).  Together with the Biomedical Advanced Research and Development Authority (BARDA), the agency also funded more than $4 million for research into the use of continuous manufacturing within pharma (6).

	So far, however, companies that have made the switch from batch to continuous processing seem to be driven more by concerns about the future and a desire to innovate, rather than by practical, day-to-day economic realities. As observers have pointed out (7), given the existing manufacturing infrastructure, relatively few companies have a compelling reason to move headlong into continuous manufacturing.

	Researchers at Singapore’s Agency for Science and Technology’s Institute of Chemical and Engineering Sciences (ICES) have been studying various aspects of continuous pharmaceutical processing, including the economics of switching from batch to continuous processing. In 2016, one team, working with GEA Pharma Systems (India), described a systematic process that process development teams could use to help them determine which processes could be most easily, and economically, shifted from batch to continuous mode (8).

	Paul Sharrat, who is leading that research effort, shared insights from that work, and his opinions on the potential of continuous pharmaceutical processing, with 

	Is continuous processing in pharma being overhyped?

 Do you think there has been too much ‘hype’ about continuous processing in pharma? Given the industry’s existing profit margins, costs for raw materials, and the way that manufacturing plants are set up, what percentage of small-molecule processes could reasonably be expected to be converted from batch to continuous?

 For small-molecule API production, perhaps half of current processes could be converted from batch to continuous and made to work at least as well as the batch equivalent, and likely better.

	The proportion of processes where there is a strong business case for making the change to continuous is likely to be much smaller. This is partly because a big financial benefit is needed to justify replacing and existing manufacturing capacity with a new continuous plant. Nevertheless, there are examples already in production where the swap was justifiable. If we look to the future and set out to deliver continuous options from day one of the development of any drug, then perhaps 80-90% continuous processes might be technically achievable, and most of those cases would be economically justified, too.

	The hype might be seen as a problem and, certainly, plenty of exaggerated and even wild claims have been made for continuous manufacturing in pharma. However, I see [some of the hype] as inevitable, and even useful, to bring academic and innovation communities on board, to create awareness of the potential of continuous processing, and a broader movement for change. 

	If we want [to establish] enthusiasm for change, then hype is hard to avoid. However, the strategic technical experts in many pharma companies know the subject well enough to be able to see through it all, and focus on reality.

 Do you see a role for continuous processing of APIs in the future? What would need to change for this to be possible and practical?

 Continuous is here to stay. I see arguments shifting from whether continuous should ever be considered [to] understanding when it will bring benefit. People are now thinking about how to embed continuous in process development and manufacturing activities.

	Three things will need to happen to move adoption forward. First, senior management must be convinced that there is sufficient potential benefit, in order to want to build a capability. If we look across the big multinational pharmaceutical companies, that case has clearly been made at some level, and most Big Pharma companies have significant research efforts in place.

	In the early stages, this research tends to be a matter of a few people getting used to how flow processing works. Then companies need to think about how to translate their own chemistries into flow and to see it working.

	To make continuous a ‘normal’ way of doing things, the capability has to be able to take a process through to manufacture, so access to new engineering capabilities is needed.

	Secondly, continuous options need to be readily available to technologists during process development. Since process development is carried out hand-in-hand with making materials for clinical trials, there is a barrier if the material used for trials is made by batch processing.

	Today, we are seeing significant numbers of continuous processes being developed by big pharma companies. Assuming that these processes succeed in clinical trials, they are very likely to progress into continuous manufacturing.

	Finally, continuous will have fully arrived when company infrastructures have adapted to leverage its potential business benefits fully. Current operating models in pharma are based on batch processing, and the infrastructure that supports batch isn’t well suited to continuous. This includes not only the manufacturing facilities but also staff skill sets, supply chains, accounting practices, and more.

	Companies are only starting to figure out the best changes that will need to be made to promote adoption of continuous processing. It is likely that manufacturing facilities will be physically smaller with more compact utility systems, more and more modern control/data systems, and more modularity. In some cases, pilot plants and manufacturing facilities may become very similar or even merge.

	How other aspects of the infrastructure will change is less clear, although change is inevitable if the full benefits of continuous processing are to be felt.

 How long has your research group been looking into continuous processing?

 I have been working on continuous with my team at ICES for nearly nine years, but started long before that while I was an academic at the University of Manchester Institute of Science and Technology in the United Kingdom. At ICES, we are already working on ‘second-generation’ technology, building on our earlier successes.

 In your research, what findings surprised you most?

 For me, the biggest surprise has been how broadly we have been able to apply continuous processing. For example, most people start tentatively with all-fluid systems and assume that, if there are solids, then batch is better. We decided to take on more challenging problems requiring solids handling and solids in flow. Despite the perceived risks, we were successful more often than not, and have expanded the range of processes for which flow could credibly be considered.

 How easily can the approach that your team outlined be adopted by commercial companies, and how would that add to the drug development time frame or cost, or would it actually save time and money?

 Our approach could readily be adopted either as is or more likely adapted to fit with other company workflows. We find the approach pretty intuitive and logical, so we believe that others could also readily learn how to do it.

 Can you please describe, step by step, the general process that you devised for assessing reactions and equipment, and how you mapped out the processes?

 We start by looking at the key processing characteristics of the system (e.g., rates of reaction, heat generation, number of phases, and mass transfer requirements). The data required needn’t be very precise but they help us to understand what the process needs from its equipment. For example, a fast, exothermic reaction will need intensive heat transfer if a serious exotherm is to be avoided. Typically, the information required comes from experiments, literature, and estimation methods. This allows a ‘sketch’ of the process to be developed, capturing the sequence and main processing requirements.

	We use the Britest tool set for process representation (9) because we find it to be effective and intuitive, but other approaches could also be used.  The result of this first stage is an assessment of potential benefit and feasibility, and a decision on whether to proceed with the project.

	The second step moves from the general to the specific. For each processing step, we look to identify the equipment that best matches the needs of the process. This is pretty much the opposite of traditional batch design, in which the process is modified and often downgraded to match the limited capabilities of a batch reactor.

	This activity starts to turn the process into a ‘flowsheet’ that would be much more recognizable to chemical engineers. We also refine our estimate of overall process performance, leading up to a more accurate costing and process understanding to enable the decision to continue towards implementation.

	The final stage is nothing more than a standard chemical process implementation project with detailed design, hazard assessment, and implementation.

 How did you factor in the potential costs of moving to continuous processing?

 The business case for a commercial company will depend on many factors--including the cost of making any changes. The critical issue is to have an idea of the feasibility and potential value early so the assessment can be made before a lot of effort is wasted. Our method allows a company to set out a high-level business case very early, in which the cost of making any changes can be accounted for.

 Generally, were there any broad rules of thumb that you found regarding types of processes, and how well they would work in continuous mode?

 In general, we found that it is easiest to convert processes that work in a single liquid phase only, and where reactions are relatively fast. Additional factors increase the complexity and difficulty, but additional fluid phases and heat transfer don’t cause much problem. When solids have to be processed, then that results in a step increase in difficulty, while difficult rheology (e.g., processes involving highly viscous or non-Newtonian fluids) and materials that are sticky or can foul equipment are almost always a serious challenge.  Another issue worth considering is the number of processing steps. A simple mix-heat-react-cool process would be much easier than a complex sequence of additions, reactions, temperature changes, and separations.

	Cases where continuous approaches won’t work

 Are there types of processes, or processes involving specific materials, that won’t work continuously?

 There are some things that can be very difficult to accommodate in continuous processes, but very few absolute barriers. What tends to happen is that the cost of making ‘difficult’ systems work becomes prohibitive when compared with batch. Some things are indicative of likely problems (e.g., systems that deposit materials on surfaces are problematic). Reactions with multiple phases and very slow kinetics can be a lot more expensive in flow than batch. Continuous solid-liquid separation can be challenging, too.

 Are there any plans to extend your research into additional problems/areas?

 We are looking to extend the range of separation techniques that can comfortably be used at the small scale that is useful in pharma. Continuous separations are easier at larger scale (e.g., the large fractional distillation columns used in the petrochemical industry). Smaller-scale fractionation is challenging because performance can be affected much more by variables such as wall effects and heat loss.

 What role do you see process intensification playing in pharmaceutical processes in the future?

 Process intensification is a great concept, but it has been a struggle to have it be adopted widely, partly because plants that are smaller are not always the most cost-effective or relevant to the business need. I do think that we will see more intensive processes in pharma in future--with both individual plants and whole supply chains driving down size and inventory where it reduces cost and improves responsiveness. However, the driver will not simply be size reduction, but, rather, fitness for the business.

	Our method actually provides a systematic approach to deliver intensified processes. Because we consider the economic viability throughout, we don’t run the risk of selecting an intensive but uneconomic design. In the end, systematic approaches to identifying good process options will prove the most effective route to intensification.

, Vol. 32, (9), September 2008.
	2. C. Challener, 

, Vol. 40 (6), June 2016.
	3. FDA Draft Guidance, 

Advancement of Emerging Technology Applications to Modernize the Pharmaceutical Manufacturing Base

, Guidance for Industry, fda.gov.
	4. “

FDA Approves Tablet Production on Janssen Continuous Manufacturing Line

,” pharmtech.com, April 12, 2016, Accessed April 4, 2017.
	5. Z. Brennan, “

FDA Allows First Switch From Batch to Continuous Manufacturing for HIV Drug

,” raps.org, April 12, 2016, accessed April 4, 2017.
	6. “

Continuus Pharmaceuticals Partners With FDA and BARDA on Continuous Processing

,” pharmtech.com, December 5, 2016, accessed April 4, 2017.
	7. G. Malhotra, “

Continuous Processing in Pharmaceutical Manufacturing: Considerations, Nuances, and Challenges

,” contractpharma.com, June 1, 2015, accessed April 4, 2017.
	8. S.K. Teoh et al., 

, 20, 2016, pp. 414-431.
	9. Britest website, 

olid Dosage Drug Development and Manufacturing


	Vol. 41
	April 2017
	Pages: s8–s11, s31

	When referring to this article, please cite it as A. Shanley, "Continuous Manufacturing: Separating Hype from Reality," 

Continuous manufacturing will not work for all pharmaceuticals, but the right infrastructure, senior management support, and planning from the earliest stages of drug development could eventually allow up to 80-90% of small-molecule APIs to be made continuously, says Paul Sharratt, head of process science and modeling at Singapore’s Institute of Chemical and Engineering Sciences.