An effective drug product must deliver a new chemical entity (NCE) to the right place, at the right time, at the right concentration for patients to benefit. The goal of the early development team is to deliver a drug candidate that is suitable for full commercial development, supported by a data package demonstrating proof of safety, tolerability, and efficacy—albeit in a relatively small number of subjects. The project team must also recommend a drug product (e.g. formulation, dose strength) that will become the medicine that is available in the marketplace. For oral medicines, the competitive nature of the pharmaceutical industry inevitably means that a once- or twice-daily dosing regimen is key to success.
Oral drug products used in first-in-human (FIH) studies are often relatively simple, with the active pharmaceutical ingredient (API) in solution, suspension, or capsule. In most early development projects, the NCE must be transitioned into a more suitable form (e.g. formulated API in capsule or tablet) that can deliver reliable and reproducible exposure to enable the proof of concept study, and subsequent progression into later development. NCEs currently emerging from the industry’s R&D pipeline, however, are often characterized with poor solubility and permeability—presenting significant challenges to optimization.1 Using the Biopharmaceutics Classification System (BCS), a recent analysis indicates that ~70% of molecules in the industry pipeline are BCS Class II (poor solubility) and a further ~20% are BCS Class IV (poor solubility and poor permeability).2
Conventional approaches to optimizing a drug product typically focus on a range of in vitro formulation systems that are screened in one or more preclinical in vivo models prior to selecting a small number of lead prototypes for testing in humans (Figure 1). The industry’s continued use of this approach is surprising given its limitations. Cycle times are extended as a consequence of the time taken to transfer between various R&D, manufacturing, testing, packaging, and clinical sites. Furthermore, translation of bioavailability between preclinical species and humans is poor (Figure 2).3
This process is also linear and rigid—formulations tested in the clinic that fail to meet the target criteria of the project must retrench back to the in vitro/preclinical phase. Since one cycle of this process can easily take up to 18 months and cost over $1.5 million, the time and financial penalties on the development project are significant.
A new paradigm
Translational pharmaceutics offers a new development paradigm for using human data to drive the rapid screening and selection of candidate drug products (Figure 3). The inherent inefficiencies of the conventional process can be overcome by using a technology platform that integrates formulation development, GMP drug product manufacturing, and clinical testing. Drug products can be manufactured and dosed in a clinical study within as little as 24 hours, with cycle times of only 10-14 days. The clinical data obtained from one candidate drug product can, therefore, be used to inform the real time manufacture and dosing of the next candidate.
The ability to respond to human data is enabled by flexible clinical protocols and the incorporation of “design space” concepts into regulatory submissions, which secure pre-approval to test a range of variable of formulation compositions, as opposed to discrete pre-defined systems. There is no requirement for any in vivo preclinical screening of formulations. This strategy ensures that all selection decisions are based upon human data, increasing the chances of success and the precision of the drug product that is finally selected.
Performance metrics from projects undertaken to date demonstrate significant benefits from this approach (Table 1). The time required to deliver an optimized drug product can be at least halved compared to the conventional process. The quantity of API consumed in this process is also reduced by 90% to 95%—delivering another significant benefit to the development project.
In summary, this approach offers great potential to reduce cycle times, decrease risks, and expedite informed decision-making in early clinical development where formulation refinements are required to optimize dose, pharmacokinetic parameters, and side-effect profiles. Since this approach can be applied to all types of oral formulations including solutions/suspension and solids, immediate release and modified release, and can encompass all types of formulation technology, it can deliver a broad impact on overall development efficiency of oral medicines.
About the Author
Dr. Mark Egerton has over 20 years experience in the pharmaceutical and biotech industry and has worked in a range of organizations from large multinational pharmaceutical companies to private venture-funded biotechnology companies.
1. Lipinski C. Poor aqueous solubility – an industry wide problem in drug discovery. Am Pharm Rev. 2002;5:82-85.
2. Hauss DJ. Oral lipid-based formulations. Adv Drug Deliv Rev. 2007;30;59(7):667-76.
3. Grass GM and Sinko PJ. Effect of diverse data sets on predictive capability DDT. 2001;835-839.
This article was published in Drug Discovery & Development magazine: Vol. 13, No. 1, January/February, 2010, pp. 16-17.
Filed Under: Drug Discovery