Quantitative Pharmacology Reduces Clinical Failure in Drug Development
Ramesh Jayaraman, Founder-Director, DoseQuantics Consulting Pvt Ltd, India
Quantitative pharmacology integrates pharmacokinetics and pharmacodynamics to guide candidate selection, optimise dosing and strengthen decisions from preclinical research through clinical trials, reducing development risks and improving therapeutic success rates.
The process of discovering and developing a drug to obtain marketing approval is lengthy (6–10 years), risky (~10% success rate), and expensive (~1 billion US dollars).
Two major reasons for drug attrition are failure to demonstrate efficacy and suboptimal PK.
The properties required for a new candidate drug (CD) to treat a disease are defined in a Target Product Profile (TPP). A key goal of the TPP is to set the dose, dose frequency, and treatment duration required to achieve the desired clinical benefit (efficacy) without adverse effects.
The preclinical programme prepares a plan to identify CDs with the PK/PD properties needed to meet the dose-related criteria set in the TPP. Applying PK/PD reasoning in preclinical development can strengthen clinical development through learning and confirmation.
Lead compound identification is a key milestone in this stage. The lead compound (LC) is a molecule with a combination of potency at the drug target and efficacy in the appropriate disease model.
The properties required for a new candidate drug to treat a disease are defined in the TPP. A key goal is to set the dose, dose frequency and treatment duration required to achieve the desired clinical benefit without adverse effects.
The PK and PD of a drug can be described (modeled) using mathematical equations that can be integrated with computational methods. Computational dynamic PK/PD models can be developed for the LC in preclinical stages by linking PK and PD models.
These dynamic PK/PD models can predict (simulate) the time course of pharmacological effects for different doses and regimens. They can provide a rationale for selecting the optimum dose and regimen to achieve maximum efficacy. Drug regulatory agencies such as the USFDA and EMEA encourage and support PK/PD modeling and simulation for decision-making.
Clinical stages
In Phase 1, the PK and safety of the CD is evaluated with escalating doses in healthy human volunteers or patients.
One goal is to determine the dose that produces the appropriate PK associated with pharmacologically active exposures (e.g. unbound Cmax, AUC) identified in preclinical studies, and to assess whether the PK supports the dose and regimen set in the TPP.
Many clinical candidates fail at this stage because they cannot demonstrate the desired PK. Therefore, it is important to predict the CD’s PK in humans with reasonable confidence before Phase 1 begins to assess its potential to meet the TPP criteria.
Physiologically-based pharmacokinetic (PBPK) models can predict PK in humans by linking drug-specific properties with system-specific properties. PBPK models can be linked to PD models to predict PK/PD time course in humans.
Combining human PK with QP data from preclinical studies can help support dose selection for Phase 2 studies. The dynamic PK/PD model can also be extended to humans to support selection of Phase 2 dose and regimens.
In Phase 2 studies, efficacy trials are conducted in a limited number of patients using different dose levels or regimens to identify the dose and regimen for further development. Quantitative analysis of PK/PD relationships with clinical efficacy, using dose-exposure-response or PK/PD modeling, can help select the dose and regimen for Phase 3 studies.
Population PK models can be developed during Phase 2 studies to understand how demographics (age, sex, race) and comorbidities (impaired liver or kidney function) influence CD PK. This helps select the right dose for the population.
In registrational (Phase 3) studies, the CD’s ability to demonstrate significant efficacy, in addition to safety, is tested in a large number of patients. This requires that the dose selected for Phase 3 be strongly supported by PK/PD reasoning from Phase 2 trials.
When the CD demonstrates clinical efficacy, confirm that robust PK/PD relationships drive efficacy. Population PK/PD models built in Phase 2 can be strengthened with Phase 3 data and used to identify appropriate doses for specific populations.
Dose and regimen decisions should be based on a strong PK/PD rationale to support marketing approval.
Use PK/PD (Quantitative Pharmacology) for critical decision-making from preclinical through clinical stages of drug development to minimise the risk of drug candidate failure. QP is the basis for selecting dose, regimen and duration of treatment for an approved drug.
Authored by:
Ramesh Jayaraman
Founder-Director
DoseQuantics Consulting Pvt Ltd