Modern drug discovery and development

Drug development is expensive

It is no secret that the development of a new medicine is a long and costly process. The cost of a medicine from invention to pharmacy shelves has been estimated to range from USD $765.9 million to $2.8 billion, depending on the therapeutic area [1,2]. The drug development process can be broadly described in the following stages:

1. Understanding the disease –> identify biological targets that can be acted upon by a drug to treat the disease
2. Search of active compounds –> screen libraries of known chemical structures to identify hit compounds that might act on the target
3. Optimisation of potential drug candidates –> evaluate and modify the hit compounds to improve their properties as active pharmaceutical ingredients
4. Formulation development –> formulate the lead drug compound into a safe and effective medicine suitable for treatment
5. Preclinical evaluation –> assess the safety and efficacy of the drug and formulation in preclinical settings to predict treatment outcome
6. Clinical trials –> evaluate the safety and efficacy of the treatment in human volunteers and patients

This is an oversimplification of the whole process and there are overlaps between these different stages. Each of these stages can take years of work by teams of scientists and continued financial investments with no guarantee of success. Research on efforts that could reduce the cost and expedite the drug development process has been an ongoing interests in the pharmaceutical science community.

Modelling & Simulation

Modelling and simulation (M&S) methods have long been used in the aerospace industry to evaluate designs of aircraft and training of pilots. However, they have not been used to a similar extent for drug development. Wouldn’t it be great if we could simulate the behaviour of a drug to help us evaluate whether that can be a medicine before we make it? This is particularly true in light of the rapid advancement of technology.

In recent years, M&S approaches have found an increasing number of applications at different stages of the drug development process. From computational chemistry to molecular dynamics simulation for drug design and screening of compound libraries, to formulation development and data analysis and modelling of trial results, different M&S approaches are increasing being utilised by drug development scientists.

Model-informed drug discovery and development

Over the past two decades, the impact of M&S in decision making in industry, regulatory, and practice settings has been extensively demonstrated in many publications. Subsequently, significant efforts have been made to appropriately frame the scope of this quantitative discipline and its role in the drug development process. This is apparent in the evolution in terminology used to describe the discipline, from M&S, to model‐based drug development and model‐based drug discovery, to the latest usage: Model-informed drug discovery and development (MID3) [3].

Here are some examples of M&S methods and their potential applications in modern pharmaceutical R&D [4].

Discovery:

• Quantitative structure-activity relationship (QSAR) –> Quantify the relationship between structural properties and activity of potential drug compounds
• Molecular dynamics (MD) –> Predict molecular interactions of drugs and other ingredients based on calculated motions of atoms and molecules
• Machine learning (ML) –> Relate drug properties to the measured activity of interest in the dataset to build predictive models

Candidate selection:

• Pharmacokinetic (PK) modelling –> Empirical modelling of drug concentration data after dosing for quantitative evaluation of drug compounds
• Physiologically-based pharmacokinetics (PBPK) –> Predict drug concentration based on system models of the species and drug properties
• Pharmacokinetic-Pharmacodynamic (PKPD) –> Relate drug concentration to effect for the dose-response relationship

Formulation:

• Physiologically-based biopharmaceutical modelling (PBBM) –>Predict drug concentration based on models of species physiology and formulation properties
• Biopharmaceutical pharmacometrics (BPMX) –> Semi-mechanistic models incorporating properties of the formulation and available data following dosing
• Computational fluid dynamics (CFD) –> Predict particle deposition in the lung based on formulation properties and airway anatomy for inhaled drug products

Clinical efficacy:

• Pharmacometrics (PMX): Relate patient demographics and clinical efficacy for personalised therapy

With the ever-increasing computing power and availability of data, these M&S methods can only be increasingly valuable in modern drug discovery and development.

Afterthoughts

We happen to be in this information era to witness the rapid advancement of technology and its application in drug discovery and development. The interests of my work revolve around the synergistic application of these M&S methods to accelerate the development of new medicines. I look forward to seeing the contribution of these new methods in our ongoing combat with difficult diseases.

References

1. Wouters OJ, et al. (2020). Estimated Research and Development Investment Needed to Bring a New Medicine to Market, 2009-2018. JAMA. https://pubmed.ncbi.nlm.nih.gov/32125404/
2. Sullivan T. (2020). A Tough Road: Cost To Develop One New Drug Is $2.6 Billion; Approval Rate for Drugs Entering Clinical Development is Less Than 12%. Policy & Medicine. https://www.policymed.com/2014/12/a-tough-road-cost-to-develop-one-new-drug-is-26-billion-approval-rate-for-drugs-entering-clinical-de.html
3. Krishnaswami S, et al. (2020). MID3: Mission Impossible or Model-Informed Drug Discovery and Development? Point-Counterpoint Discussions on Key Challenges. Clin Pharmacol Ther. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7158219/
4. Sou T, et al. (2021). Contemporary Formulation Development for Inhaled Pharmaceuticals. J Pharm Sci. https://pubmed.ncbi.nlm.nih.gov/32916138/