Cleo Bern Hartley is a pharma consultant, former pharma analyst, and research scientist.

Cleo Bern Hartley

Cell and gene therapies (CGTs) offer significant advances in patient care by helping to treat or potentially cure a range of conditions that have been untouched by small molecule and biologic agents. Over the past two decades, more than 20 CGTs have been approved by FDA in the United States and many of these one-time treatments cost between US$375,00 and US$2 million a shot (1). Given the high financial outlay and patient expectations of these life-saving therapies, it is essential that manufacturers provide integrated services across the whole of the supply chain to ensure efficient biomanufacturing processes and seamless logistics to reduce barriers to uptake.

The following looks at the who, what, when, and why of biomanufacturing and logistics in CGTs in the bio/pharmaceutical industry in more detail.

According to market research, the global gene therapy market will reach US$9.0 billion by 2027 due to favorable reimbursement policies and guidelines, product approvals and fast-track designations, growing demand for chimeric antigen receptor (CAR) T cell-based gene therapies, and improvements in RNA, DNA, and oncolytic viral vectors (1).

In 2020, CGT manufacturers attracted approximately US$2.3 billion in investment funding (1). Key players in the CGT market include Amgen, Bristol-Myers Squibb Company, Dendreon, Gilead Sciences, Novartis, Organogenesis, Roche (Spark Therapeutics), Smith Nephew, and Vericel. In recent years, growth in the CGT market has fueled some high-profile mergers and acquisitions including bluebird bio/BioMarin, Celgene/Juno Therapeutics, Gilead Sciences/Kite, Novartis/AveXis and the CDMO CELLforCURE, Roche/Spark Therapeutics, and Smith & Nephew/Osiris Therapeutics.

Many bio/pharma companies are re-considering their commercialization strategies and have re-invested in R&D to standardize vector productions and purification, implement forward engineering techniques in cell therapies, and improve cryopreservation of cellular samples as well as exploring the development of off-the-shelf allogeneic cell solutions (2).

The successful development of CGTs has highlighted major bottlenecks in the manufacturing facilities, and at times, a shortage of raw materials (3). Pharma companies are now taking a close look at their internal capabilities and either investing in their own manufacturing facilities or outsourcing to contract development and manufacturing organizations (CDMOs) or contract manufacturing organizations (CMOs) to expand their manufacturing abilities (4). Recently, several CDMOs—Samsung Biologics, Fujifilm Diosynth, Boehringer Ingelheim, and Lonza—have all expanded their biomanufacturing facilities to meet demand (5).

A major challenge for CGT manufacturers is the seamless delivery of advanced therapies. There is no room for error. If manufacturers cannot deliver the CGT therapy to the patient with ease, the efficacy of the product becomes obsolete. Many of these therapies are not ‘off-the-shelf’ solutions and therefore require timely delivery and must be maintained at precise temperatures to remain viable. Thus, manufacturers must not only conform to regulations, but they must also put in place logistical processes and contingency plans to optimize tracking, packaging, cold storage, and transportation through the product’s journey. Time is of the essence, and several manufacturers have failed to meet patient demands, which have significant impacts on the applicability of these agents.

Several CAR T-cell therapies have now been approved; however, research indicates that a fifth of cancer patients who are eligible for CAR-T therapies pass away while waiting for a manufacturing slot (6). Initially, the manufacture of many of these autologous products took around a month, but certain agents can now be produced in fewer than two weeks (7). Companies are exploring new ways to reduce vein-to-vein time (collection and reinfusion) through the development of more advanced gene-transfer tools with CARs (such as transposon, CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) among others, and the use of centralized organization with standardized apheresis centers (5). Others are exploring the use of the of allogeneic stem cells including Regen Biopharma, Escape Therapeutics, Lonza, Pluristem Therapeutics, and ViaCord (7).

Several gene therapies have also been approved, mainly in the treatment of rare disease (8). Many companies are evaluating novel gene therapy vectors to increase levels of gene expression/protein productions, reduce immunogenicity and improve durability including Astellas Gene Therapies, Bayer, ArrowHead Pharmaceuticals, Bayer, Bluebird Bio, Intellia Therapeutics, Kystal Biotech, MeiraGTx, Regenxbio, Roche, Rocket Pharmaceuticals, Sangamo Therapeutics, Vertex Pharmaceuticals, Verve Therapeutics, and Voyager Therapeutics (8).

While many biopharma companies have established their own in-house CGT good manufacturing practice (GMP) operation capabilities, others are looking to decentralize manufacturing and improve distribution by relying on external contracts with CDMOs and CMOs such as CELLforCURE, CCRM, Cell Therapies Pty Ltd (CTPL), Cellular Therapeutics Ltd (CTL), Eufets GmbH, Gravitas Biomanufacturing, Hitachi Chemical Advances Therapeutic Solutions, Lonza, MasTHerCell, MEDINET Co., Takara Bio, and XuXi PharmaTech (6, 9, 10).

The top 50 gene therapy start-up companies have attracted more than $11.6 billion in funds in recent years, with the top 10 companies generating US$5.3 billion in series A to D funding rounds (10). US-based Sana Biotechnology leads the field garnering US$700 million to develop scalable manufacturing for genetically engineered cells and its pipeline program, which include CAR-T cell-based therapies in oncology and CNS (Central Nervous System) disorders (11). In second place, Editas Medicine attracted $656.6 million to develop CRISPR nuclease gene editing technologies to develop gene therapies for rare disorders (12).

Overall, CGTs have attracted the pharma industry’s attention as they provide an alternative route to target diseases that are poorly served by pharmaceutical and/or medical interventions, such as rare and orphan diseases. Private investors continue to pour money into this sector because a single shot has the potential to bring long-lasting clinical benefits to patients (13). In addition, regulators have approved several products and put in place fast track designation to speed up patient access to these life-saving medicines. Furthermore, healthcare providers have established reimbursement policies and manufacturers have negotiated value- and outcome-based contracts to reduce barriers to access to these premium priced products

On the downside, the manufacture of CGTs is labor intensive and expensive with manufacturing accounting for approximately 25% of operating expenses, plus there is still significant variation in the amount of product produced. On the medical side, many patients may not be suitable candidates for CGTs or not produce durable response due to pre-exposure to the viral vector, poor gene expression, and/or the development of immunogenicity due to pre-exposure to viral vectors. Those that can receive these therapies may suffer infusion site reactions, and unique adverse events such as cytokine release syndrome and neurological problems both of which can be fatal if not treated promptly (14).

Despite the considerable advances that have been made in the CGT field to date, there is still much work needed to enhance the durability of responses, increase biomanufacturing efficiencies and consistency and to implement a seamless supply chain that can ensure these agents are accessible, cost-effective, and a sustainable option to those in need.

McKinsey Insights on Cell and Gene Therapy

J. Chapman, “FDA Addresses Cell and Gene Therapy Manufacturing Challenges,” Redica Systems, Nov. 5, 2020.

N. Pike, “Build vs. Buy Dilemma–Economics of Manufacturing Cell-based Therapies,” 

, Bioinsights publishing Limited, July 28, 2022.

P. Van Arnum, “CDMOs Invest in Biomanufacturing, Cell- & Gene-Therapy Manufacturing,” 

BioSpace, “Allogeneic Stem Cell Therapy Market: Therapeutics Companies Segment to Offer Attractive Opportunities,” 

Binocs, “Industrializing the Next Generation of Cell and Gene Therapies,”
Whitepaper, 

P. Van Arnum, “Cell and Gene Therapies: A Manufacturing View,” 

C. Hildreth, “Cell Therapy CDMO–Role of Contract Manufacturing for Cell Therapies,” 

Medical Startups, “Top Gene Therapy Companies,” 

Editas Medicine, Our Research and
Pipeline, 

D. Crean, “The Cell & Gene Therapy Market: Coming into Its Own,” 

Cleveland Clinic, “CAR T-Cell Therapy: Procedure, Prognosis & Side
Effects,” 


Volume 46, Number 10
October 2022
Pages: 54-55

When referring to this article, please cite it as C.B. Hartley, "Growth in Cell and Gene Therapy Market," 

Articles

Biopharma focuses on streamlining biomanufacturing and supply chain issues to drive uptake of cell and gene therapies.

Growth in Cell and  Gene Therapy Market

Artificial intelligence (AI) is a disruptive force and promises to help speed up drug identification; improve patient selection; create digital twins; improve manufacturing; tailor marketing material; enhance customer engagement; predict chronic diseases; and support health equity (1). However, there are some disadvantages with AI that need to be taken into consideration.

The following article discusses AI in the bio/pharmaceutical industry and its effect on who, what, when, and why its adoption is of interest.

In 2021, AI start-ups attracted $66.8 billion in investment (+108% year-on-year) and healthcare AI accounted for nearly 20% of total funding (2). Healthcare AI company Deep Mind (a Google Health company) was in pole position followed by IBM Watson Health and Oncora Medical. However, many companies such as Babylon Health and Caption Health are waiting to jump on the podium (3).

Investment in AI has stimulated growth in start-ups, specialized products, initial public offering (IPOs), and acquisitions. Exscientia, one of the first companies to evaluate AI-designed drugs in Phase I clinical trials listed on the NASDAQ with a valuation of US$3 billion in October 2021 (4). In December 2021, Benevolent AI signed an agreement with the SPAC, Odyssey Acquisition to accelerate its AI-enabled clinical pipeline and reached unicorn status with a pre-money valuation of €1.1 billion (US$1.24 billion) and a post-valuation of up to €1.5 billion (US$1.69 billion) (5).

Not surprisingly, AI start-ups have attracted a lot of attention from biopharma with Pfizer, Takeda, and AstraZeneca leading the way in terms of deals, followed by Novartis, Bristol Myers Squibb (BMS), Roche, Janssen, Merck KGaA, Boehringer Ingelheim, Bayer, GlaxoSmithKline (GSK), and Sanofi (6). A number of partnerships have already been announced in 2022 between AstraZeneca/Benevolent AI (7), Sanofi/Exscientia (8), Shinogi/Elix (9), Shinogi/NEC Corporation (10), Astrogen (11), Ono Pharmaceutical (12), and Teijin Pharma with Iktos (13).

However, all is not rosy in the AI garden. Concerns have been raised regarding the accuracy of AI-supported software used to diagnose and guide treatment (14, 15), highlighting the importance of high-quality training data to prevent AI bias and, in some cases, AI-enabled systems may be more beneficial to augment human decisions rather than as standalone tools (14, 16). In addition, the ethical implications of using AI analytics and the wider issues associated with healthcare data storage and data security continues to be debated, emphasizing the need for strict regulatory oversight in this area (17).

Although many biopharma companies have established their own in-house AI capabilities, some still rely on partnerships with AI vendors—Atomwise, BenevolentAI, ConcertAI, Exscientia, Google Quantum AI, Iktos, Insilico Medicine, MicroSoft, Recursion Pharma, and Sensyne Health—to support their drug discovery programs and identify novel drug targets, biomarkers, and new chemical entities for clinical valuation (18, 19).

According to market research (2021), the global AI in pharma market is expected to grow from US$935 million in 2021 to US$1236 million in 2022 at a compound annual growth rate of 32.3% driven by the launch of new start-ups and new services (20). Pharma is looking at leveraging AI beyond drug discovery and development to transform the way they perform clinical trials and interact and communicate with stakeholders. This has fuelled a new breed of AI start-ups—AiCure, Avaya, Deep Lens, Owkin, UNlearn.AI, and VeriSIM Life—to service this need (21, 22).

Overall, AI is being adopted on a large scale by pharma and healthcare companies due to its capacity to bring intelligence to repetitive tasks. It is well-suited to managing substantial amounts of healthcare data and can be deployed quickly, cheaply, and flexibly across the supply chain to problem-solve and tailor solutions to meet business requirements and market demands. For instance, in a review article Paul Debleena et al. (2021) stated, “AI can also be implemented for the regulation of in-line manufacturing processes to achieve the desired standard of the product. Artificial Neural Network (ANN) based monitoring of the freeze-drying process is used, which applies a combination of self-adaptive evolution along with local search and backpropagation algorithms. This can be used to predict the temperature and desiccated-cake thickness at a future time point (t + Δt) for a particular set of operating conditions, eventually helping to keep a check on the final product quality” (23).

Nevertheless, an AI-driven approach requires a different business mind-set and culture, one where management must buy-in to AI-generated insights to drive the decision-making process. AI relies on leveraging historical data to train the algorithms, so the adage ‘junk in, junk out’ is very apt and the use of high-quality data alongside robust governance processes and human oversight will be essential to instil trust and increase accountability. The buck stops with humans/the CEO and not machine.

Many experts argue that if pharma does not invest in AI it will fall behind because a rule-based AI model can help analyze large quantities of data to support decision-making, drive efficiencies, and increase profitability. Aran Maree, chief medical officer, The Janssen Pharmaceutical Companies (J&J) posted on LinkedIn that, “Single cell datasets are transforming the field of drug discovery. By leveraging AI and Machine learning, we’re able to analyse individual cells, identify specific genes involved in disease progression—and then identify potential ways to better treat these diseases … my company announced that we are joining a new pre-competitive consortium, led by Rancho BioSciences, that will help us leverage the power of single cell datasets to drive the discovery and development of innovative medicines. The mission of the consortium is to find a common industry standard around how single cell datasets are created and formatted. This is an exciting example of how we can use the power of data science to advance precision medicine and shape the future of healthcare to benefit patients everywhere” (24). Expect to see and hear more partnership announcements as the bio/pharmaceutical industry feels its way forward.

1. L. Kwo, “Contributed: Top 10 Use Cases for AI in Healthcare,” 

2. CB Insights, State of AI Global 2021, 2021.

3. QWay Healthcare, “Top Trends in AI in Healthcare for 2022,” 

4. iMedia, “AI Pharmaceutical Industry Welcomes IPO Again, with a Market Value of Over US$3 Billion,” 

5. BenevolentAI, “Benevolent AI and Odyssey Acquisition Business Combination,” Press Release, Dec. 6, 2021.

6. Global Data Healthcare, “Big Pharma Forging More Partnerships with AI Vendors for Drug Discovery, 

7. Benevolent AI “BenevolentAI Announces 3-Year Collaboration Expansion with AstraZeneca Focused on Systemic Lupus Erythematosus and Heart Failure,” Press Release, Jan. 13, 2022.

8. Exscientia, “Exscientia and Sanofi Establish Strategic Research Collaboration to Develop AI-driven Pipeline of Precision-Engineered Medicines,” Press Release Jan. 7, 2022.

9. Elix, “Elix, Inc. Begins Collaboration With Shionogi & Co., Ltd. on Elix Synthesize (AI Drug Discovery Module) for Verification of Practical Retrosynthetic Analysis,” Mar. 25, 2022.

10. Shionogi, “Shionogi and NEC collaborate on hep B vaccine development,” Press Release, Apr. 18, 2022.

11. Iktos, “Collaboration with Astrogen to Use AI Platform,” Press Release, Jan. 5, 2022.

12. Iktos, “Collaboration With Ono in Artificial Intelligence for New Drug Design,” Press Release, Mar. 30, 2022.

13. Iktos, “Iktos and Teijin Pharma to Co-Develop New Technology for Small Molecule Drug Discovery,” Press Release, Apr. 5, 2022.

15. University of Cambridge, V. Antun, et al., On Instabilities of Deep Learning in Image Reconstruction and the Potential Costs of AI, 

16. ByteBridge, “Why the High-Quality Training Data is so Important to AI Machine Learning?” 

Becoming Human: Artificial Intelligence Magazine

17. Lexalytics, AI in Healthcare: Data Privacy and Ethics Concerns, Feb. 10, 2021.

18. M. Ayers, et al., “Adopting AI in Drug Discovery,” 

19. K.K. Mak, M.K. Balijepalli, M.R. Pichika, 

21. K. Parkins, “Five AI-enhanced Clinical Trial Start-ups to Watch in 2021,” 

22. IDEA Institute on Artificial Intelligence, AI Communication Facilitation between Stakeholders, July 15, 2021.

When referring to this article, please cite it as C.B. Hartley, “Big Pharma in the Balance,” 

Is AI a panacea for pharma’s productivity gap?