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Optimum API performance for oral delivery forms

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Matt Mollan and Julien Meissonnier, Catalent provide expertise on strategies to optimise API performance for oral delivery dosage forms

According to a recent report1, the average drug development cost today is around $1.4 billion. If time costs or expected returns that investors forego while a drug is in development are further added into the costs, the total cost to develop a drug rises to $2.6 billion. An additional $312 million is spent on post-approval R&D activities such as new formulations, new dosage strengths and regimens and monitoring safety and long-term side effects in patients. The higher drug development costs could be explained by the increasingly challenging nature of drug candidates due to the inherent complexity of activating the target receptors, increased focus on chronic and degenerative diseases, as well as rigorous regulatory requirements and the drive towards patient-centric drugs.

What challenges does this cause in the development process? A recent drug delivery landscape survey2 by the Catalent Applied Drug Delivery Institute shows that drug development cost, lengthier development cycles and identifying a suitable delivery platform are the top three business challenges faced by formulation scientists and R&D managers. The key challenge mentioned was that the majority of the compounds entering the development stage are poorly soluble2. Their insight echoes the current biopharmaceutics classification system (BCS), according to which ~70% of new chemical entities (NCEs) are either poorly soluble in water, have low cell permeability or both. Safety, therapeutic efficacy, and stability also dominated as the top drug formulation challenges currently faced by R&D. Specifically, dissolution issues, API degradation and crystallisation/precipitation issues were found to be the top stability challenges faced by the formulation scientists.

How can the industry respond to these challenges and make the drug development process more efficient to create better therapies while maintaining quality? A crucial step in this process can be addressing these challenges at the early stage of drug development. Recent innovations have provided techniques and tools to address all the biopharmaceutical challenges including bioavailability, stability, manufacturability and safety challenges faced by development scientists in today’s industry. The need is to better design the drug development process so that it is both scientifically rigorous and data driven; is simultaneously more efficient and effective in systematically examining all the relevant techniques available (in parallel to save time) and is then immediately followed by conducting feasibility studies and rapid prototyping to select the best possible formulation and delivery system match to overcome each molecule’s unique set of challenges.

Table 1 describes the biopharmaceutical challenges and the tools available to resolve them.

Table 1

Challenges

Solutions

Biopharmaceutical /

Bioavailability Challenges

Stability challenges (physical and/or chemical)

Industry experts agree that a single approach cannot resolve the challenges for all drug molecules in R&D today. These issues have to be addressed on a case by case basis, keeping in mind the unique physicochemical and biopharmaceutical characteristics of the API. High throughput salt, crystal-form and co-crystal screening can be an enabler in speeding up drug development at the early stages. To optimise the API’s stability and solubility, these screening platforms, along with pre-formulation studies, can be an efficient and practical way to evaluate and select the most suitable solid-form for an API.

Needless to say, the selection of appropriate formulation approach during the early stage of product development involves several challenges, including limited API supply, the need for rapid turnaround, and finite development time. These constraints have triggered the need for new modelling and predicting techniques. For example, a thermodynamic solubility modeling approach can provide the required correlation between experimental and predicted solubility data that can be useful in selecting vehicles for initial formulation design faster3. This novel approach can help overcome challenges in labour and material requirements during traditional dosage formulation experiments, resulting in the opportunity to perform dosage form selection in the early phases of drug development.

New techniques have also been developed to improve small batch size handling processes to resolve the challenges posed by the low amount of API often available in early drug development. One of the approaches adapted to lipid based drug delivery systems involves adapting the input parameter values, such as process parameters and tooling on the industrial scale machine.4

These results in manufacturing early development batches (ie preclinical) applying from the very beginning of a project the adequate quality process parameters while maintaining adequate yield for each unit operations. This solution avoids cost-intensive scale-up steps, enables developing Quality by Design settings at the very early stage of a programme (ie Phase I) and yields faster and better outcomes for the drug product. The development of a new project with only a low amount of API available is possible because product losses have been identified for each step of the process and an optimisation of the tooling involved in this kind of small production has been successfully performed.

With all the new drug formulation tools and better understanding of the target receptors, it is expected there will be a reduction in the demise of molecules during the development process and more molecules proceeding to the pre-clinical animal pharmacokinetics (PK), toxicity  or first-in-human (FIH) studies. However, integrating a suite of drug development tools under the same umbrella, to enable the selection of the most stable and effective ‘developability’ form, will further enhance the current approach. This will result in creating an efficient process that will give each molecule the best chance to succeed. This multidisciplinary platform can be based on a three-pronged approach.

Employing this scientific Developability Classification System strategy in the early drug development process can significantly reduce potential risks and contribute to overall time and cost savings. To summarise, an all-inclusive, cross-functional, multi-discipline approach will optimise the API performance, enabling robust manufacturing with the goal of putting a cap on the ever increasing cost of drug development.

References:

  1. Tufts CSDD 2014 Cost Study, Tufts Center for the Study of Drug Development.  http://csdd.tufts.edu/news/complete_story/pr_tufts_csdd_2014_cost_study
  2. The 3rd annual drug delivery landscape survey was sponsored by Catalent Applied Drug Delivery Institute. For more information, visit www.drugdeliveryinstitute.com
  3. FORMULATION DEVELOPMENT - Overcoming Early Phase Development Challenges & Optimizing Formulations With a Minimal Amount of API, Irena McGuffy, Drug Development & Delivery, June 2015. http://www.drug-dev.com/Main/Back-Issues/FORMULATION-DEVELOPMENT-Overcoming-Early-Phase-Dev-939.aspx#sthash.quHrNccB.dpuf
  4. Softgel Capsules Low Batch Size Optimization on Industrial Equipment, Vincent Plassat & Guillaume Enderlin, Catalent Pharma Solutions, CRS Annual Conference, 2015
  5. The Developability Classification System: Application of Biopharmaceutics Concepts to Formulation Development, James M. Butler, GSK R&D Harlow, JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 99 (4940-4954), NO. 12, DECEMBER 2010
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