The costly and lengthy nature of drug development has long been accepted as a given. But can industry do something about it? Catalent argues that it could, if the current linearity of the development process were replaced with a multidisciplinary approach at the outset
There has been, and by its nature always will be, a linear nature to drug discovery – where there are defined stages of progression, such as from discovery, through pre-clinical phases, and into clinical development. As such, the time taken to launch a new drug is lengthy, and consequently, costly.
Figures vary greatly as to the true cost of a drug’s development; however, a recent report1 gave an average cost of US$1.4bn, with a true cost, when incorporating time costs or expected returns that investors forego while a drug is in development, of $2.6bn.
One way to reduce the time spent on development is to carry out certain stages in parallel. However, this involves planning from the outset, and for cross-functional teams across several areas of research and development, common goals have to be established to gain efficiency that translates into both time and monetary savings.
Molecules are becoming more challenging, and ever-tightening regulatory requirements are increasing the cost of development
The nature of drug candidates has evolved over time. Molecules are becoming more challenging, and ever-tightening regulatory requirements are increasing the cost of development. In a recent survey,2 conducted by the Catalent Applied Drug Delivery Institute, formulation scientists and R&D managers identified the top three business challenges they faced as drug development costs, lengthier development cycles, and identifying a suitable delivery platform.
The survey echoed issues associated with data highlighted by the current bio-pharmaceutics classification system (BCS),3 according to which, around 70% of new chemical entities (NCEs) are either poorly soluble in water, have low cell permeability, or both. As a formulation scientist, these physical challenges are major hurdles to have to overcome within the development process, as without effective control of dissolution, active pharmaceutical ingredient (API) degradation and solid state stability, the chances of a drug progressing are severely compromised.
Moreover, beyond solubility/permeability challenges, the drug development pathway is littered with new hurdles that will reveal themselves progressively, such as concentration dependent adverse events and complex dosing frequencies, potentially further limiting the future success of the drug product. With a view to working in the most efficient manner to save time and money, while also addressing the specific needs of each development candidate, a strategy to bring together all available tools and expertise to identify and select the most stable and effective drug form and delivery vehicle as early as possible within the development process is one way to enhance the current approach.
This approach removes some of the linearity of development by establishing a multidisciplinary approach from the outset, and not relying on each discipline to work around challenges carried over from previous activities. As such, any team would draw on expertise from scientists with backgrounds in diverse areas such as physical chemistry, analytical chemistry, automation, synthetic chemistry, physical pharmacy, crystal engineering and informatics to work together from the outset to identify issues before they arise and have an impact on development.
It is vital to have rapid screening technologies to provide the data to drive the development towards configuring the most stable and efficient drug form
Each new molecule brings with it new, unpredictable challenges, so it is vital to have rapid screening technologies to provide the data to drive the development towards configuring the most stable and efficient drug form. These studies are crucial to optimise the performance of the API initially, and provide data on solubility and affinity patterns (i.e. stability) and multiple solid state attributes (i.e. particle morphology) and allow evaluation of those attributes in light of the final outcomes.
Additionally, to streamline the development, it is important to consider what may be the most suitable delivery technology for the molecule at the earliest available opportunity and, more importantly, the delivery technology that would offer the largest design space.
By introducing orientative formulation screening studies early in the development of formulations, this will ensure that any chosen API form can be assessed and optimised to match the right drug delivery enhancement technology and remain stable during product development operations. By taking time to assess each molecule and employing a scientific ‘developability classification system’ strategy4 early in the drug development process, the tools available to formulation and development scientists increase the chances of more molecules progressing to pre-clinical animal pharmacokinetics, toxicity or first-in-human studies.
Recent innovations have provided a wide variety of techniques and tools to address all the biopharmaceutical challenges faced by development scientists in today’s industry. These include bioavailability, stability, manufacturability and safety challenges. To make the development process as efficient as possible, and to allow both rigorous science and accurate data to drive the advancements towards the optimal drug form, all relevant and available techniques must be systematically examined and funnelled by feasibility studies and rapid prototyping.
Screening in parallel, and having the capability to handle small batch size manufacturing, reduces the time spent in converting experimental data to prototype to enable a feedback loop to the process. At this stage, where a limited quantity of API may be available, it is essential to use the material in the most efficient manner. However, any small-scale processing must be validated to be translatable to scale-up facilities.
As not one single approach exists to overcome all of the biopharmaceutical challenges presented by drug candidates, it is vital for formulation scientists to have access to all relevant tools available, providing sufficient differentiation to handle a variety of combined challenges (biopharmaceutical, physico-chemical etc.).
For bioavailability issues in the early phase of development, the use of one, or a combination of the following techniques, can lead to enhanced exposure, enabling secure progression through Phase 1 SAD escalation studies: particle size engineering; solid dispersion/solution formulations (i.e. hot-melt extrusion); lipid based drug delivery systems; and salt/co-crystal formation. Those techniques could be combined at a later stage, with enhanced delivery techniques enabling further optimisation of the drug product design: controlled and/or modified release formulations, with further formulation options reducing variability.
Overcoming stability challenges – physical and/or chemical – can be achieved by altering the formulation’s composition (i.e. through changing the nature of the excipient), optimising the API crystal form, optimisation of the manufacturing process, or by the selection of an optimal packaging system. All of these issues have to be addressed on a case-by-case basis, bearing 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.
There are also a number of in silico models that can be undertaken in parallel to the screening. These predictive tools are especially useful when API material is limited, but also provide vital information that can help shape the formulation design.
Employing a scientific ‘developability classification system’ strategy in the early drug development process by engaging an all-inclusive, multi-disciplinary approach can optimise API development
Solubility, seen as a key formulation challenge, can be predicted by a thermodynamic solubility model that can provide the required correlation between experimental and predicted solubility data. This information can assist in selecting vehicles for initial formulation design, resulting in the opportunity to perform dosage form selection in the early phases of drug development.
Once a candidate is identified, the subsequent steps again call for suitable and efficient manufacturing capabilities, where early development batches need to be easily scaled up for clinical programmes and yields can be maintained to maximise API material consumption. Through the use of parallel development, with input from many disciplines, where common goals have been shared from the outset, intensive and costly scale up revision programmes can be avoided.
In summary, drug development is an expensive industry, where time dictates much of the economics; by saving time in areas of development and working more efficiently, costs can be reduced. Employing a scientific ‘developability classification system’ strategy in the early drug development process by engaging an all-inclusive, multi-disciplinary approach can optimise API development. By bringing together expertise from all relevant R&D functions, and enabling them with the broadest tools and innovative technologies in formulation and drug delivery, the ever-growing challenges that drug molecules present can be overcome.
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. www.drugdeliveryinstitute.com
3. Patel ND, Patel KV, Panchal LA, Shukla AK, Shelat PK., Int. J. Pharmaceut. Biolog. Arch. 2011; 2(2) 621–629
4. James M. Butler, GSK R&D Harlow, J. of Pharma Sciences, Vol. 99 (4940–4954), No 12