Translational PK/PD for the Development of Novel Antibiotics—A Drug Developer’s Perspective

• Published in: Antibiotics (Basel) Vol. 13; no. 1; p. 72
• Main Authors: Bissantz, Caterina, Zampaloni, Claudia, David-Pierson, Pascale, Dieppois, Guennaelle, Guenther, Andreas, Trauner, Andrej, Winther, Lotte, Stubbings, William
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.01.2024
• Subjects: Antibiotics; Antimicrobial agents; Bacteria; Bacterial infections; Clinical trials; drug development; Drug dosages; Drug resistance; Effectiveness; FDA approval; Gram-negative bacteria; Infections; Infectious diseases; Pathogens; Patients; Pharmacodynamics; Pharmacokinetics; PK/PD index; Pneumonia; PTA; R&D; regulatory; Regulatory approval; Research & development; Risk reduction; Robustness; Sulbactam; Tazobactam; Tetracycline; Tetracyclines; Translation; translational PK/PD; Maryland; United States > US; semi-mechanistic PK/PD modeling; PK/PD index; translational PK/PD; in vitro; regulatory; drug development; PTA; animal model; antibiotics; resistance
• ISSN: 2079-6382; 2079-6382
• DOI: 10.3390/antibiotics13010072

Antibiotic development traditionally involved large Phase 3 programs, preceded by Phase 2 studies. Recognizing the high unmet medical need for new antibiotics and, in some cases, challenges to conducting large clinical trials, regulators created a streamlined clinical development pathway in which a lean clinical efficacy dataset is complemented by nonclinical data as supportive evidence of efficacy. In this context, translational Pharmacokinetic/Pharmacodynamic (PK/PD) plays a key role and is a major contributor to a “robust” nonclinical package. The classical PK/PD index approach, proven successful for established classes of antibiotics, is at the core of recent antibiotic approvals and the current antibacterial PK/PD guidelines by regulators. Nevertheless, in the case of novel antibiotics with a novel Mechanism of Action (MoA), there is no prior experience with the PK/PD index approach as the basis for translating nonclinical efficacy to clinical outcome, and additional nonclinical studies and PK/PD analyses might be considered to increase confidence. In this review, we discuss the value and limitations of the classical PK/PD approach and present potential risk mitigation activities, including the introduction of a semi-mechanism-based PK/PD modeling approach. We propose a general nonclinical PK/PD package from which drug developers might choose the studies most relevant for each individual candidate in order to build up a “robust” nonclinical PK/PD understanding.