For the VP of Clinical Operations (or a leader at a startup or midsize biotech or pharma company), planning a Phase I or II oncology trial in the U.S. requires navigating a complex regulatory landscape while pushing the boundaries of innovation. The decisions you make at this early stage can have a lasting impact on the success of your study, especially when using cutting-edge treatments like antibody-drug conjugates (ADC) or cell and gene therapies.
Targeted treatments like ADCs are often described with various terms that reflect their precision and innovation in oncology. At the ESMO 2024 conference, several notable advancements regarding ADCs and cell and gene therapies were highlighted.
Antibody-Drug Conjugates (ADCs)
Daiichi Sankyo presented updates on its ADC portfolio, with a focus on datopotamab deruxtecan for non-small cell lung cancer (NSCLC) and DS-9606, a claudin 6-targeting ADC for various solid tumors. The TROPION-Lung01 trial showed promising survival outcomes for datopotamab deruxtecan compared to standard chemotherapy (docetaxel). In addition, DS-9606 demonstrated potential therapeutic benefits with a favorable safety profile in early studies.
Claudin-targeted ADCs were also a major point of discussion, with promising results in solid tumors. DS-9606a, targeting claudin 6, showed no severe toxicities and early efficacy in heavily pretreated patients. Another claudin 18.2-targeted ADC, SHR-A1904, demonstrated a 55.6% objective response rate in gastric cancer patients, highlighting its potential in difficult-to-treat cancers.
Cell and Gene Therapies
While ADCs were a major focus, ESMO 2024 also showcased advancements in cell and gene therapies, though these were less prominently discussed than ADCs. However, the growing momentum around precision oncology, particularly through targeted therapies like ADCs and other biologics, remains a critical frontier in the development of more effective cancer treatments.
These findings reinforce the importance of targeted treatments like ADCs in advancing precision oncology, offering new hope for patients with difficult-to-treat cancers, such as NSCLC and HER2-expressing breast cancers.
Leveraging the latest approaches and technologies can improve targeting and efficacy but also include new cost and safety elements to plan for. Here are essential tips to help you streamline your targeted treatment trial while also leveraging the power of AI to optimize outcomes.
For early-phase oncology trials, your objectives and endpoints drive every aspect of the study design. In Phase I, the primary goal is often safety and dosage optimization, while Phase II focuses on efficacy and further safety evaluation. It’s crucial to align your trial’s objectives with regulatory requirements from the start. Ensure that your endpoints reflect not only scientific rigor but also what matters most to your stakeholders.
For complex therapies like ADCs or cell and gene therapies, endpoint selection may need to address unique pharmacodynamics or immune responses. Incorporating biomarkers and pharmacokinetic data early on can also enhance the clinical narrative of your novel therapy.
AI has rapidly become an invaluable tool in clinical trials, particularly in oncology. From patient recruitment to data analysis, AI-driven platforms can accelerate timelines and provide insights that were previously unattainable. In early-phase oncology trials, identifying the right patients can be a major bottleneck. AI can help optimize patient selection by analyzing large datasets to identify patients with specific genetic markers or disease characteristics suited for your therapy.
AI-enabled monitoring and data analytics can also provide real-time insights into patient safety and efficacy signals, allowing for adaptive trial designs. This flexibility can be particularly beneficial when working with cutting-edge treatments like cell and gene therapies, where patient responses can be unpredictable.
Oncology trials often struggle with patient recruitment due to stringent inclusion and exclusion criteria, particularly in trials involving novel therapies like ADCs or cell and gene therapy. Implementing AI-powered tools to match patients to trials based on genomic data, previous treatments, and overall health status can significantly reduce recruitment time. Beyond recruitment, AI can also help predict patient retention risks and enable personalized interventions to keep patients engaged throughout the trial.
In addition, decentralized trials powered by digital health tools can improve access for patients by minimizing the need for in-person visits. This approach has been particularly beneficial for trials in rare cancers and therapies where patient populations are often small and geographically dispersed.
Planning for the production and distribution of novel therapies like ADCs or cell and gene therapies is more complex than traditional small molecules. Cell and gene therapies, for example, often require individualized manufacturing processes, which can introduce logistical challenges. Ensure that you have a robust supply chain strategy in place to manage everything from material procurement to final delivery to clinical sites. Double check with your CRO to ensure that they have the relevant supply chain management experience.
Working with innovative therapies means navigating a more complex regulatory environment. Early and proactive communication with the FDA is essential to ensure that your study design aligns with regulatory expectations.
Partnering with a CRO experienced in oncology and advanced therapies ensures that regulatory submissions are handled efficiently and with the highest standards of quality. Medelis brings decades of experience in managing oncology trials, including ADCs and cell and gene therapies, to ensure that your trial not only meets regulatory requirements but is also designed for success from the ground up.
To schedule a complimentary protocol review, contact us.