Clinical Researcher—October 2024 (Volume 38, Issue 5)

SPECIAL FEATURE

Dr. Ilona Baraniak-Lang; Dr. Anna-Lena Amend

 

 

 

Advances in the cancer treatment space have renewed hope for breakthroughs with personalized cancer vaccines (often also called personalized immunotherapies). More recently, there have been promising results in a number of areas, including pancreatic cancer, melanoma, and non-small cell lung cancer (NSCLC).{1} According to analysts, significant growth is expected for cancer vaccines, with one report noting that the global market for cancer vaccines should grow from $10.21 billion in 2023 to $30.16 billion by the end of 2033.{2}

The principle behind personalized cancer vaccines is simple: the cancerous cells and healthy cells of the individual are genetically distinct.{3} The genetic alterations in tumor cells, specifically point mutations, often lead to the formation of cancer-specific neoantigens, which in turn can be utilized as highly specific targets for personalized immunotherapy. As personalized immunotherapy is tumor specific, it offers potentially novel, less toxic treatment options for patients{4} compared to many existing treatment options that affect both tumor and healthy cells, such as chemotherapy.

Another important feature of personalized cancer vaccines is the ability to elicit potent and durable anti-tumor immune response as well as creating immunological memory{1} and preventing cancer relapse.

Moreover, personalized cancer vaccines are not only used as a standalone treatment, but are also co-developed as reliable adjuvant therapies for immune checkpoint inhibitors (ICIs), as the combination has a synergistic effect as well as the potential to overcome the ICI resistance in patients who are unresponsive.{5} A growing body of evidence demonstrates activity of the personalized cancer vaccines not only against highly immunogenic and immune-responsive tumors (“hot tumors”) but also against non-immunogenic (“cold tumors”), which are normally resistant to immunotherapies.{6} Importantly, due to novel mode of action, personalized cancer vaccines represent hope for patients who have exhausted all other therapeutic options.

There are several options for developing a personalized immunotherapy product, including DNA, RNA, or peptides.{4} Additionally, cell-based products, such as autologous dendritic cell vaccines and viral vectors as a vaccine platform, are an emerging field.{7}

A plethora of clinical trials for (personalized) cancer vaccines are underway globally, with several in late-stage development.{8} However, as of now, very limited approved products are readily available for patients. In the European Union (EU), so far, no therapeutic cancer vaccine has been authorized. In the U.S., the Food and Drug Administration (FDA) has approved three therapeutic vaccines, with only one product, Provenge® (sipuleucel-T, approved in 2010) being a personalized product.{9} Provenge is a first-generation dendritic cell vaccine, which has, for example, been shown to improve median overall survival (OS) in advanced prostate cancer patients.

Regulatory Discrepancies

Despite the promise, our experience shows that there are many challenges that innovators need to overcome from a development, regulatory, and chemistry, manufacturing, and controls (CMC) perspective.

As a novel class of products, personalized cancer vaccines lack clear regulatory guidance, with regulatory standards and guidances still largely to be developed, which can result in a discrepancy in regulatory oversight and opinion of the regulatory agencies with regards to cancer vaccine development.{10} As such, certain approaches might be accepted by one agency but rejected by the other, which can result in divergent developments and even opposing regulatory opinions, making it very difficult for developers to follow a global approach.

Moreover, there are some major differences between the EU and U.S. in the classification of such products. While the FDA has introduced the term “therapeutic cancer vaccines” and classifies all of these products as such,{11} in the EU, there is no such specific classification available. The classification (and associated regulation) of these products depends on each product’s composition. For peptide or synthetic DNA/RNA products, products will likely be considered as vaccines and chemical medicinal products. However, nucleic acid-based products that are non-synthetic, dendritic cell vaccines or products using a viral vector are considered an advanced therapy medicinal product (ATMP) and ATMP regulations apply.{12} However, with an upcoming change in regulation, synthetic nucleic acids will likely also be considered ATMPs, which means the majority of cancer vaccines in the EU would be classified as ATMPs.{13}

The Role of Artificial Intelligence and Machine Learning

There are also major challenges with identifying the right target for the vaccine to ensure a good immunologic response. Here, artificial intelligence (AI), machine learning, and other bioinformatic tools are key.{14} To identify tumor-specific neoantigens, both healthy and tumor tissue samples are collected from cancer patients and subsequently analyzed in the lab by high throughput technologies, such as next-generation sequencing (NGS). Next, an (often proprietary) AI algorithm is used to identify unique antigens that are only expressed by the specific tumor and, at the same time exclude any targets present in healthy cells. This is critical, since inclusion of neoantigens that closely resemble targets in healthy cells could lead to autoimmunity and serious side effects for patients receiving a personalized cancer vaccine.{4}

With Moderna and Merck’s candidate mRNA-4157, for example, AI has been key in determining how the vaccine should be designed to target an individual patient’s cancer. Moderna expects the FDA will want to inspect its algorithm, given that AI is key to its development program.{15}

This does create some complexities, given the novel nature of AI-based development. However, further guidance on the use of AI and medicinal products is expected, with the FDA planning to release guidance on AI and machine learning in drug development this year.{16}

Given this complex and fast-changing environment, a multidisciplinary approach that brings together experts in vaccines, ATMPs, AI and machine learning, and knowledge of the regulatory requirements in both the U.S. and EU will be key.

Tackling CMC Challenges

One of the most complex issues for developers of personalized cancer vaccines to address is CMC (chemistry, manufacturing, and controls).

Firstly, it is important to note, that the currently established pharmaceutical paradigm was designed for drugs that are produced in bulk rather than for personalized medicines, where the product is different for each patient. As such, many currently existing regulations cannot be applied, or the traditional approaches must be modified and endorsed by the overseeing regulatory body.

Secondly, a fast turnaround is needed from biopsy to administration—typically under three months. This is key since these products are targeting late-stage cancer patients, so timing is critical. Nevertheless, such short timelines must cover several complex steps such as sample biopsy, drug-design, drug manufacture under Good Manufacturing Practice conditions, quality control, and drug distribution to a clinical site, all of which might be located in different geographies, and therefore requiring complex logistics. Streamlining the activities is extremely challenging since each product is unique and no common reference standard can be applied. Therefore, optimization of the processes, manufacture, and quality control of finished products needs to be performed, to a large extent, on the level of well-designed platform technology.

Use of Complex Bioinformatics Tools for Designing Investigational Medicinal Products

As previously noted, precision medicine follows a nonconventional production process, starting with the identification, selection, and preparation of patient-specific input material using NGS techniques and the vaccine design using AI and machine learning.{17} These are the areas that pose potential challenges for companies that are unfamiliar with detailed standards and requirements.

All NGS analysis must be conducted on validated protocols, with qualified equipment, and by trained staff. Processes should be accredited according to globally recognized standards, including, for example, ISO 15189{18} for quality management specific to medical laboratories, ISO 17025{19} testing and calibration laboratory standards, College of American Pathologists (CAP) laboratory standards,{20} and onsite audits.

However, since NGS is well-established in clinical trials, these requirements are unlikely to be a major obstacle. The bigger challenge lies with AI and machine learning, since there is currently no internationally approved regulatory framework for assessing the use of these innovative algorithms in the design of these types of products. It is therefore difficult to predict exactly what will need to be provided. There is also a discrepancy between the major authorities. The FDA requires high-level information, including on all databases used to train the model and all detailed information regarding the bioinformatic tools used in this in silico pipeline,{21} while other regulators might not require similar level of detail on these novel bioinformatic tools.

Additionally, the informal advice given by the regulators is that the in silico pipeline should remain unchanged once the clinical trial application is submitted. The challenge here is that, because the system is self-learning, usually, acquired data are used to train and optimize it. Therefore, there needs to be a careful balance between the modifications and training of the system (which may also further improve it) and keeping it in a steady state, so that it is possible to make a comparison between clinical trials. To address this, developers will need to discuss with the regulators to what extent and when certain modifications can be introduced.

Potency

Another big challenge for CMC is how to establish the potency assay. These are normally used to quantitatively measure the biological activity of the drug in the disease-relevant system.{22} However, with personalized cancer vaccines there isn’t a disease-relevant model as it will differ from patient to patient. Here, a potency assay would need to measure the neoantigen-specific T cell responses elicited by the vaccine, but to obtain a meaningful readout, these T cells would need to be collected from an already vaccinated patient. As such, a standard potency assay is not feasible and alternative solutions must be discussed with regulators beforehand.

Sterility Testing

One potential bottleneck is sterility testing. This is required for the release of finished products, but standard sterility testing takes at least two to three weeks to complete. This is critical, since the timeframe from biopsy to treatment should remain as short as possible to treat these late-stage cancer patients.

There are, however, several alternative options. One is to follow, where applicable, the principles of real-time release testing (more specifically parametric release), where testing is not performed on each batch (or each individual vaccine) but rather is dependent on demonstrating that pre-determined, validated sterilizing conditions have been achieved throughout the manufacturing process.{23} Here, experience shows that submission of evidence of successful validation of the manufacturing process and documentation on process monitoring during manufacturing, without direct measurement of quality attributes, is accepted.

Another approach might be to consider a “sterility by design” approach, leveraging a risk-based approach, where each step of the manufacturing process is designed to minimize any risk of microbial contamination.{24} Here, the enhanced product knowledge and process understanding, coupled with the use of quality risk management principles and the application of an appropriate pharmaceutical quality system, is critical to assure sterility of such products.

Another option would be to use alternative rapid sterility testing,{25} though this typically requires bringing in another service provider, which may not help to shorten the timeline.

In some situations, regulators may be open to allowing distribution to clinical sites without the final sterility test, on condition the results are provided as soon as possible and ensuring the product is not used at the clinical site before final release. In such cases, well-defined measures would need to be employed, such as detailed standard operating procedures, to ensure compliance with this approach.

Stability Barriers

The next big CMC challenge is stability testing. Since vaccines are personalized and can only be produced after enrolment of a patient in the trial, “traditional” stability testing is not feasible. Developers must present well thought-out solutions to the regulators. Some approaches that we have seen regulators being open to include:

• Performing a range of studies where the manufacturer tests a whole spectrum of possible product make-up. For example, peptides where the developer may test the most hydrophobic and the most hydrophilic ones. Any other peptide that is produced using this system would fall within the range, which, experience shows, would provide confidence that the products will be stable.
• Investing in stability of several batches manufactured by the same process, for example, two engineering and five clinical batches.
• Leveraging prior knowledge of the platform technology. Specifically, with mRNA, the manufacturer may have stability data on similar products that use similar manufacturing processes and similar formulations. Our experience has found that this knowledge can be leveraged to provide greater assurance that the product will be stable.

Changing Regulatory Environment

The regulatory environment for personalized cancer vaccines continues to evolve alongside the science. So far, only a few guidances have been developed, and even when the regulators do release guidelines, the highly dynamic nature of the field means they are likely to be constantly updated.

Another big challenge is the lack of global harmonization, especially between major geographic regions, which means approaches accepted by some agencies may not be accepted by others. This can make it a difficult research space in which to navigate and define a harmonized global strategy.

It is therefore important that developers regularly engage with the authorities and seek their endorsement for any proposed solutions. Developers should also closely monitor guidances, position papers, and news in the field. Additionally, to address discrepancies between authorities, it is important to seek parallel or joint scientific advice—especially within the EU, where it is possible to leverage and use the opinion of one regulatory agency to inform another agency about the current plans. 

Disclaimer

The information provided in this article does not constitute legal advice. PharmaLex and Cencora, Inc., strongly encourage readers to review available information related to the topics discussed herein and to rely on their own experience and expertise in making decisions related thereto.

References

1. Drew L. 2024. How does a cancer vaccine work? Nature. https://www.nature.com/articles/d41586-024-00841-y
2. Cancer Vaccines Market Size Envisioned at USD 30.16 Billion by 2033. Towards Healthcare. https://www.towardshealthcare.com/insights/cancer-vaccines-market-sizing
3. What is cancer? National Cancer Institute. https://www.cancer.gov/about-cancer/understanding/what-is-cancer
4. Xie N, Shen G, Gao W, Huang Z, Huang C. 2023. Neoantigens: promising targets for cancer therapy. Sig Transduct Target Ther8(9). https://doi.org/10.1038/s41392-022-01270-x
5. Wang B, Han Y, Zhao Q, Wang H, Wei J, Meng L, Xin Y, Jiang X. 2023. Overcoming acquired resistance to cancer immune checkpoint therapy: potential strategies based on molecular mechanisms. Cell & Bioscience 13 (article 120). https://cellandbioscience.biomedcentral.com/articles/10.1186/s13578-023-01073-9
6. Ouyang P, Wang L, Wu J, Tian Y, Chen C, Li D, Yao Z, Chen R, Xiang G, Jin Gong J, Bao Z. 2024. Overcoming cold tumors: a combination strategy of immune checkpoint inhibitors, Frontiers in Immunology 13. https://doi.org/10.3389/fimmu.2024.1344272
7. Dillman RO, Nistor GI, Keirstead HS. 2023. Autologous dendritic cells loaded with antigens from self-renewing autologous tumor cells as patient-specific therapeutic cancer vaccines. Human Vaccines & Immunotherapeutics19(1). https://doi.org/10.1080/21645515.2023.2198467
8. ClinicalTrials.gov
9. PROVENGE (sipuleucel-T). FDA. https://www.fda.gov/vaccines-blood-biologics/cellular-gene-therapy-products/provenge-sipuleucel-t
10. Vaccines Europe pipeline review 2023. Vaccines Europe. https://www.vaccineseurope.eu/wp-content/uploads/2023/11/VaccinesEurope-PipelineReview2023.pdf
11. Clinical Considerations for Therapeutic Cancer Vaccines. FDA. https://www.fda.gov/media/82312/download
12. Reflection paper on classification of advanced therapy medicinal products. EMA. 2015. https://www.ema.europa.eu/en/documents/scientific-guideline/reflection-paper-classification-advanced-therapy-medicinal-products_en.pdf-0
13. Defining Gene Therapy Medicinal Products in the EU. 2024. DIA Global Forum. https://globalforum.diaglobal.org/issue/march-2024/defining-gene-therapy-medicinal-products-in-the-eu/
14. Hargreaves B. AI Enables Individualized Cancer Vaccines. 2024. Biospace. https://www.biospace.com/ai-enables-individualized-cancer-vaccines#:~:text=Advances%20with%20AI,on%20specific%20neoantigens%20as%20targets
15. ‘We’re open for business’: FDA’s Peter Marks says agency ready to review novel cancer vaccines despite unknowns. 2024. Fierce Biotech. https://www.fiercebiotech.com/biotech/were-open-business-fdas-peter-marks-says-agency-ready-review-novel-cancer-vaccines-despite
16. FDA plans to release AI drug development guidance this year. 2024. Regulatory Focus. https://www.raps.org/news-and-articles/news-articles/2024/5/fda-plans-to-release-ai-drug-development-guidance
17. Fan T, Zhang M, Yang J, Zhu Z, Cao W, Dong C. 2023. Therapeutic cancer vaccines: advancements, challenges, and prospects. Sig Transduct Target Ther8 (article 450). https://doi.org/10.1038/s41392-023-01674-3
18. https://www.iso.org/standard/76677.html
19. https://www.iso.org/ISO-IEC-17025-testing-and-calibration-laboratories.html
20. Aziz N, Zhao Q, Bry L, Driscoll DK, Funke B, Gibson JS, Grody WW, Hegde MR, Hoeltge GA, Leonard DGB, Merker JD, Nagarajan R, Palicki LA, Robetorye RS, Schrijver I, Weck KE, Voelkerding KV. 2015. College of American Pathologists’ laboratory standards for next-generation sequencing clinical tests, Arch Pathol Lab Med. https://pubmed.ncbi.nlm.nih.gov/25152313/
21. Using Artificial Intelligence & Machine Learning in the Development of Drug & Biological Products, Discussion Paper. FDA. https://www.fda.gov/media/167973/download?attachment
22. What you should know about potency assays. https://www.biopharma-excellence.com/2020-5-4-what-you-should-know-about-potency-assays/
23. Guideline on Real Time Release Testing (formerly Guideline on Parametric Release). EMA. https://www.ema.europa.eu/en/documents/scientific-guideline/guideline-real-time-release-testing-formerly-guideline-parametric-release-revision-1_en.pdf
24. Jaworski D. 2024. Microbial Control During Low-Risk Aseptic Processing. PDA. https://www.pda.org/pda-letter-portal/home/full-article/microbial-control-during-low-risk-aseptic-processing
25. Alternative Methods for Control of Microbiological Quality. http://www.uspbpep.com/ep60/5.1.%206.%20alternative%20methods%20for%20control%20of%20microbiological%20quality%2050106e.pdf

Dr. Ilona Baraniak-Lang, Associate Principal Consultant at PharmaLex, is a vaccinologist and virologist, and specializes in global regulatory affairs strategies. She has successfully supported more than 200 vaccine, ATMP, and other biopharmaceutical development projects, with clients including big pharma, subject matter experts, start-ups, governmental institutions, non-profit organizations, and academia.

Dr. Anna-Lena Amend, Consultant at PharmaLex, is a molecular biologist and specializes in global regulatory affairs strategies, mostly for ATMPs/cell and gene therapies, as well as personalized cancer vaccines and other innovative products. Typical clients encompass start-ups, subject matter experts, big pharma, and academia.