FDA’s Project Optimus: A new era in oncology drug dosing

The oncology drug development landscape is evolving rapidly, driven by the deployment of targeted therapies in precision medicine and regulatory initiatives like the FDA’s Project Optimus. These advances are reshaping how pharmaceutical and biotechnology companies approach clinical trial design, with a focus on patient-centric dosing strategies.

This article explores how innovations in precision medicine are reshaping clinical trials, followed by a discussion on Project Optimus and its impact on dose optimisation. It also covers strategies for drug developers who have yet to identify a biomarker, helping them advance their programs effectively. Finally, we explore how partnering with contract research organisations (CROs) can assist companies in navigating these changes in early-phase oncology clinical trials.

Redefining clinical trial design

Precision medicine is revolutionising oncology by delivering therapies tailored to individual patients based on genetic and molecular factors. This approach aims to improve treatment efficacy (compared to cytotoxic chemotherapy), minimise toxicity, and necessitates an evolution in clinical trial methodologies.

Genetic, molecular, and lifestyle factors in precision medicine

1. Genetic factors

• Mutations or alterations in tumour DNA (eg, EGFR mutations in lung cancer or HER2 amplification in breast cancer) are key targets of precision medicine.
• Genetic predispositions, such as BRCA mutations in hereditary cancers, influence treatment options and inform preventive measures.

2. Molecular factors

• Molecular markers, such as protein expression and signalling pathway activation, also guide therapy choices. For example, PD-L1 expression predicts the response to immune checkpoint inhibitors.
• Advances in molecular profiling techniques, including next-generation sequencing (NGS), enable comprehensive tumour characterisation and further refine the precision medicine options available to patients.

These components work synergistically to create personalised treatment plans that deliver improved outcomes for patients.

From one-size-fits-all to biomarker-driven studies

Historically, oncology clinical trials have employed a ‘one-size-fits-all’ approach, testing therapies on large populations that are now known to be molecularly heterogeneous. While this strategy has led to the development of effective therapies, it has often failed to provide clinical benefit to the majority of patients, who belong to genetically distinct subgroups within the broader cancer indication. In practice, many patients received therapies that were not aligned with their tumour biology, leading to a lack of efficacy and unnecessary side effects.

Biomarkers and their central role

Biomarkers enable a more precise selection of patients based on a demonstrated improvement in the response rate to a specific targeted therapy. These measurable indicators, such as genetic mutations and molecular signatures, are now considered integral to the clinical success of targeted therapy development.

When a biomarker has not yet been identified

For therapies that have not been formally linked to a biomarker, developers can still advance their first-in-human programmes by:

• Early-phase exploration: Testing therapies in a diverse ‘all-comer’ patient population to observe patterns or clusters of response in subgroups of patients.
• Tissue sampling and archiving: Collecting and storing tumour and blood samples for retrospective biomarker discovery.
• Adaptive trial designs: Building flexibility into trial protocols that allow for enriching cohorts if biomarkers are identified mid-study.

Innovative trial designs: Basket trials

Basket trials fall under the category of Phase 2 trials. They evaluate a single therapy across multiple cancer types or indications. This design can be applied to different indications that share a common genetic characteristic (also known as patient selection biomarkers), focusing on tumour biology rather than the original tumour location. It provides the flexibility to address tumour heterogeneity and maximises resource efficiency (and thus optimises drug development timelines) by simultaneously studying several patient cohorts within a single trial framework, each with its own customised statistical power.

Adaptive trial designs for ongoing improvement of efficacy focus

Adaptive trial designs utilise Bayesian rather than frequentist statistics. They allow for real-time adaptation of patient recruitment based on emerging interim data. These flexible methodologies are particularly valuable in oncology trials, where the understanding of biomarker relevance often evolves during the course of a study. As such, they are ideal for exploratory efficacy trials. Their implementation, however, requires well-defined, pre-specified decision-making criteria.

Through continuous refinement of study parameters, the main benefit of adaptive Bayesian designs is the ongoing improvement of patient selection as a basis for “proof-of-concept” efficacy demonstration.

Challenges of small, focused cohorts

Precision oncology trials typically involve biomarker-defined subsets of historically larger patient populations, which can make recruitment challenging. Organising global trials relies on collaborative networks, which are critical for addressing these recruitment challenges. Leveraging extensive global site networks can help efficiently meet study recruitment objectives, ensuring trials are executed within the required development timelines.

The role of real-world data

Real-world data (RWD) is becoming integral to oncology trials. These data sources provide critical insights into patient outcomes in everyday settings, supplementing traditional clinical endpoints. By incorporating RWD, researchers gain a more comprehensive understanding of a therapy’s efficacy and safety across diverse populations while enriching evidence for regulatory submissions.

Project Optimus: Rethinking dose optimisation

While precision medicine focuses on selecting the right patients, Project Optimus emphasises identifying the right dose to administer to patients. In traditional oncology drug development, dose escalation (Phase 1) trials aim to identify the maximum tolerated dose (MTD) – an approach designed to maximise drug exposure in an attempt to maximise tumour response (or size reduction). This was historically associated with a significant toxicity cost, often leading to adverse effects, reduced patient quality of life, and, not infrequently, minimal survival gains.

Project Optimus advocates for the identification of an optimal biological dose (OBD) that balances efficacy, safety, and tolerability. This framework mandates robust dose-ranging studies early in development, akin to the standard research paradigm used in therapeutic areas other than oncology.

Hence, Project Optimus requires developers to adopt more rigorous, data-driven approaches to dose optimisation. Key considerations include:

• Comprehensive dose exploration: Early-phase trials must characterise doses beyond the singular focus on MTD. This approach underlies the identification of the OBD, backed by both clinical efficacy and drug tolerability data.
• Pharmacologically-guided dosing: Integrating pharmacokinetics (PK), pharmacodynamics (PD), and translational biomarkers into dose selection tailors drug administration regimens that maximize the therapeutic index of a drug.
• Advanced statistical approaches: Modern statistical approaches utilising Bayesian and other methods enable efficient analysis of complex dose-response data helping developers make informed decisions about dosing.

Leveraging CRO expertise in dose optimisation

One option for developers seeking to implement Project Optimus in their oncology drug development is to partner with expert CROs. These partnerships can provide the extensive experience needed for navigating the challenges posed by Project Optimus, offering end-to-end support:

• Strategic trial design: Designing early-phase trials that seamlessly incorporate dose-ranging studies, ensuring a thorough exploration of the dose-response relationship.
• Regulatory alignment: Expertise and experience in meeting FDA and EMA guidelines, ensuring compliance and minimising delays.
• Data-driven insights: Leveraging advanced modelling techniques can help deliver actionable recommendations to refine dosing regimens and optimise patient outcomes.
• Scientific advisory board guidance: Advisory board experts can provide strategic input to help clients integrate patient-centric dosing principles from the outset.

Driving the future of oncology drug development

Precision medicine is transforming the oncology landscape. At the same time, regulatory initiatives like the FDA’s Project Optimus are driving the adoption of dose optimisation strategies. These advances require a reimagining of clinical trial design and execution.

By partnering with CROs, developers can access expertise in biomarker-driven studies, adaptive trial designs, and global patient recruitment, ensuring that innovative therapies progress efficiently through their development stages. Leveraging these partnerships can help empower the biotech industry to accelerate the development of transformative oncology therapies, shaping the future of cancer care.

References

1. Redig, A. J., & Jänne, P. A. (2015). Basket Trials and the Evolution of Clinical Trial Design in an Era of Genomic Medicine. Journal of Clinical Oncology, 33(9), 975–977.
2. Barker, A. D., et al. (2009). Adaptive Clinical Trial Design in Oncology: An Overview. Clinical Pharmacology & Therapeutics, 86(1), 97–100.
3. U.S. Food and Drug Administration. (2024). Project Optimus: FDA’s Initiative to Reform Oncology Dose Optimization. FDA.gov
4.  biotx.ai GmbH. (2024). How causal artificial intelligence is revolutionizing the pharmaceutical industry. Nature