ÃÛÌÒ´«Ã½

Facebook
  1. Home
  2. Insights
  3. Blog
  4. Solving common challenges to develop oncology combination therapies

Solving common challenges in developing oncology combination therapies

There has been a proliferation of cancer therapies recently with more than 60 oncology approvals by the FDA in 2024, including 11 first-in-class therapeutics.1 Specialised and combination treatments are transforming the oncology market and shifting the focus from standard of care (SoC) chemotherapies and radiation therapies. New combinations of therapies include molecular targeted treatments and radiopharmaceuticals. Investment in combination therapies is expected to continue, and most future cancer patients will be treated with combination therapies. 

ÃÛÌÒ´«Ã½ conducted a survey of oncology developers in North America and Europe to understand the impact of this shift in focus. In this article we look at some of the unique challenges oncology developers encounter during therapeutic development. We suggest ways to de-risk combination therapy clinical development here, and in more detail in our whitepaper.

Assessing the risks of combination therapies

Some oncologists suggest that identifying highly effective combinations of existing therapies may be more clinically beneficial for patients than developing new monotherapies.2 But the entry criteria for a combination therapy may be stricter with lengthier enrolment periods and fewer eligible patients approved for treatment post-approval. Combination therapies also have a higher potential for adverse reactions. Different drugs may not be compatible and combination therapies could increase adverse events from drug-drug interactions.3 In preclinical and early clinical development crucial first step is assessing the possibility of adverse drug interactions when selecting appropriate therapy combinations.

Identifying optimal cancer drug combinations is increasingly difficult with the rapidly rising number of potential therapy combinations. Artificial intelligence (AI) and advancements in high-throughput screening are proving crucial to identify and choose optimal cancer drug combinations. AI-driven frameworks are being researched as tools to predict which combination therapies are synthetically lethal, and to clarify associated biological processes.4

Optimal dose determination

Traditional methods of rule-based dose selection are not suitable for dose selection of combination therapies. Oncology developers should use sensitive, model-based methods of dose determination when they have selected an optimal therapeutic combination. Identifying the optimal biologic doses of both therapies should account for both efficacy and toxicity, through dose selection protocols. 

Some drugs may be more potent in combination than as a monotherapy. The optimal dose of a monotherapy drug may be higher than when the same drug is delivered as part of a combination therapy. Being able to lower the dose of a drug with toxic side effects may improve the safety profile of a combination therapy compared to when the drug is administered separately. 

Biomarker selection

Biomarker development for measuring the efficacy of combination therapies is a notable challenge for combination therapy development. Accurate biomarkers that predict a participant¡¯s response to treatment is a prerequisite to identifying the participants who will benefit most from combination therapy. It may be necessary to redefine biomarkers and biomarker thresholds used in monotherapy outcomes assessments when the same therapy is used in combination.

Conclusion

In an increasingly sophisticated and crowded therapeutic oncology environment, clinical development and commercialisation become evermore complex. Every respondent to our survey encountered challenges with at least one clinical trial element. Undoubtedly the 60 oncology therapies that the FDA approved in 2024 also faced their own challenges. Effective collaboration with partners, vendors and trial sites can transform insurmountable challenges into successful clinical development. 

Download our whitepaper to learn more about de-risking clinical development in oncology.

References:

1 FDA Approvals in Oncology: October-December 2024. American Association for Cancer Research (AACR). . Published 2025. Updated 3 January 2025. Accessed 17 January, 2025. 

2 Loi S, Settleman J, Joyce JA, et al. The next big questions in cancer research. Cell. 2023;186(8):1523-1527. 

3 Liu B, Zhou H, Tan L, Siu KTH, Guan X-Y. Exploring treatment options in cancer: tumor treatment strategies. 

4 Wang J, Wen Y, Zhang Y, et al. An interpretable artificial intelligence framework for designing synthetic lethality-based anti-cancer combination therapies. J Adv Res. 2024;65:329-343.

 

This blog is an edited version of ¡®Combination Therapies May Be the Future of Oncology ¨C How Can We Navigate Development Challenges Today?¡¯ which was first published on BioPharmaTrend on 9 Feb 2025.

In this section

Connect with us