A drug-drug interaction occurs when the presence of a drug affects the pharmacokinetics/pharmacodynamics of another drug. This is due to a change (increase of decrease) in the levels and activity of the victim drug. FDA has recently published two guidance on in-vitro and clinical DDI studies. The in-vitro DDI guidance focuses on the in-vitro experimental approaches to study the DDI involving drug metabolizing enzymes (DMEs) and transporters. The clinical DDI guidance discusses the conduct of clinical DDI studies with respect to timing and design, interpretation of DDI studies and managing DDIs in patients.
Drug-drug interactions have a mechanistic basis and may occur due to change in metabolism by or change in transport (inhibition or induction). DME inhibition has been widely studied and is considered broadly to be of two types: 1. Reversible inhibition and 2. Irreversible inhibition. Transporter inhibition is usually reversible, although a few cases of time-dependent transporter inhibition have been recently reported.
DDI prediction has become a cornerstone of drug development process. The capability to predict DDI early in drug development is essential and could be of great advantage. This could be achieved by in-vitro DDI studies. Once, a DDI is established, one could proceed with a clinical DDI study in human subjects or utilize a mechanistic approach by using physiologically-based pharmacokinetic (PBPK) model. PBPK model being an in-silico technique, has the advantage of drastically reducing the drug development costs. KinderPharm LLC utilizes tools such as PK-Sim® and MoBi® (Bayer software) to apply a whole-body concept and predict the impact of DDI. PK-Sim® uses an integrated database which contains anatomical and physiological parameters for humans and laboratory animals. These parameters are used in the PBPK model to predict the change in drug concentrations and pharmacokinetic parameters due to DDI. PK-Sim® can also generate virtual populations including pediatric populations, which could be used to predict DDI in these populations or to evaluate the change in exposure due to age. The mechanistic basis of such prediction makes it possible to evaluate DDI due to inhibition/induction of a specific or multiple enzymes and transporters. An alternative to PBPK modeling is to conduct a clinical DDI study.
A typical clinical DDI study usually involves two drugs, one is the probe substrate while the other is the interacting drug. The interaction could be due to an inhibition or induction of a common metabolic or transport pathway. The subjects in a DDI study receive treatment A (probe substrate) in the first period and treatment B (probe substrate + interacting drug) in the second period. By comparing the pharmacokinetic parameters in the two periods, the impact of DDI is evaluated, usually in terms of change in drug clearance and area under the curve (AUC). A maximum inhibition/induction is achieved in these studies to evaluate the highest impact of DDI on probe substrate levels.
The KinderPharm Pharmacokinetic modeling team specializes in and has a wide experience with:
- understanding the metabolic profile and pharmacokinetics of the drug,
- gap analysis of drug metabolism and pharmacokinetic data (in-vitro and in-vivo),
- interpretation of in-vitro metabolism and transport data to better understand DDI,
- interpretation of in-vivo data metabolism and pharmacokinetic data in laboratory animals (ex. radioactive studies to assess clearance pathways),
- understanding the effect of food on pharmacokinetics of orally administered drugs,
- DDI prediction using a highly mechanistic and robust PBPK model,
- simulations using PBPK model (ex. for dose adjustments to prevent DDI), and
- design, analysis and interpretation of clinical DDI studies
The KinderPharm pharmacokinetic team has been involved in DDI prediction studies and PBPK modeling in a variety of therapeutic areas including oncology, anti-infectives, CNS, GI respiratory, immunology, endocrinology/metabolic diseases.