De-risking Drug Development: Key Chemistry, Manufacturing, and Controls (CMC) and Physiologically Based Pharmacokinetic (PBPK) Approaches in Early Development 

In drug development, early strategic planning is crucial to minimizing risks, optimizing formulations, and setting up candidates for success. In a recent presentation given at the 2024 AAPS PharmSci 360 Conference, Certara’s Deven Shah, Head of CMC, and David B. Turner, Senior Scientific Advisor & Head of Mechanistic Oral Absorption Modelling, shared insights into using CMC activities and PBPK modeling to streamline development and reduce attrition rates.  

Here’s a summary of best practices from their talk on the importance of integrating CMC and PBPK early to address common challenges in drug development. 

The Goal: De-risk Drug Development Early 

Drug development is complex, with high attrition rates often driven by formulation and manufacturability issues. To address these challenges proactively, it’s important to develop a sound understanding of CMC properties and leverage predictive technologies such as PBPK modeling early on. This can improve compound selection, identify approaches to enhance bioavailability, and anticipate potential issues long before clinical trials. Key goals include: 

1. Planning with the End in Mind

• Lead Optimization: Begin with the goal of selecting compounds with optimal physico-chemical properties, setting up the project for long-term success. 
• Toxicology Support: Ensure that early formulations are suitable for toxicity testing, a critical step in transitioning to clinical development. 
• Holistic View in Early Development: A cross-disciplinary approach helps identify and address risks in meeting the key attributes in the target product profile (TPP) related to dosage form, shelf life, and efficacious exposures, earlier on.    

2. Addressing CMC Challenges

Laying the foundation for a robust product entail understanding the molecule and developing a formulation that can facilitate the clinical testing for addressing key patient unmet needs.   Early development should demonstrate that the product is: 

Stable

Formulations must withstand varied storage and testing environments. 

Orally Bioavailable

Oral formulations should maximize absorption. 

Manufacturable

The compound and formulation must be suitable for manufacturing at scale. 

Enabling

The product should provide the means for testing the clinical proof of concept via delivery of optimal dose to the target site. Enhances therapeutic effectiveness, addresses any bioavailability and stability challenges  

Incorporating these elements early in development helps mitigate the risks of failure due to formulation issues and allows for a smoother transition through each phase of drug development. With advances like PBPK modeling, these properties can be optimized through predictive tools, helping developers make informed decisions about formulation strategies tailored to the drug’s characteristics.   

Following work packages were discussed in the talk:

1. Early CMC Characterization 

Early evaluations of physicochemical properties, such as solubility, stability, and scalability, set the foundation for robust product development. Identifying the optimal salt or polymorph can further improve solubility and bioavailability, mitigating risks early on.  Understanding bio-pharmaceutics profile of the asset (e.g. BCS/DCS Class) further helps in understanding the key challenges for oral absorption and identifying an optimal and tailored formulation approach for overcoming these challenges.   

2. PBPK Modeling Integration

Virtual Patient Simulations: PBPK models simulate drug absorption and distribution across various organ systems, using virtual patient populations to predict drug behavior. This modeling can help anticipate first-in-human dosing, drug-drug interactions, and absorption challenges.

Informed Decisions with in Silico Trials: In silico simulations provide an opportunity to make adjustments before physical trials, saving time and resources. This predictive approach supports dose optimization, formulation tweaks, and early toxicology assessments.

3. Case Study Insights

One case study included in the presentation focused on the use of in vitro models to prioritize a lead candidate for a p-38 inhibitor series, allowing an effective in vitro ranking. Another case study demonstrated how PBPK modeling and a developability classification system (DCS) framework helped optimize a DCS IIb compound with limited bioavailability, employing strategies like particle size reduction and bio-enhancement.

4. Holistic Monitoring and Continuous Model Refinement

As the drug progresses, PBPK models are continuously updated with experimental data. This iterative refinement enhances accuracy, allowing early detection of red flags like solubility, bioavailability, or stability issues to name a few. By addressing these proactively, teams can avoid setbacks in later phases.

Key Takeaways for Success 

1. Start Strong with CMC and PBPK activities and approaches

Early integration of CMC and PBPK activities helps identify risks that could delay or derail development, making for a more resilient pipeline.

2. Know your molecule

Thorough developability evaluation of the molecule attributes to select drug candidates with higher probability of success during drug development.

3. Foster Collaboration

Cross-functional collaboration ensures a holistic view, addressing formulation and bioavailability challenges before they become critical issues.

4. Use Predictive Modeling to Avoid Pitfalls

PBPK modeling allows for virtual trials, reducing the need for extensive preclinical studies. It can also support clinical study waivers when appropriate, expediting progress.

5. Refine Models for Iterative Improvements

PBPK models are continuously refined with new data, maintaining the accuracy of predictions and reducing reliance on trial-and-error adjustments, ultimately strengthening trial outcomes.

Best Practices for De-risking Early in Development – Red flags to watch 

By planning with the end goal in mind, leveraging PBPK modeling, and tackling CMC factors early on, there is a higher likelihood of success in drug development, paving the way for efficient and effective candidate progression through the pipeline. 

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