Rob van Wijk
Group Leader, LACDR
Rob van Wijk is group leader of the Translational Immuno-Pharmacology research group at the division of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden University. In his research group, state-of-the-art translational pharmacology models are developed and applied to address pressing questions in global health and infectious diseases. Van Wijk is an expert in preclinical-to-clinical translational pharmacology with experience in both experimental, computational, and clinical disciplines at Leiden University, Uppsala University, and the University of California, San Franscisco. His research group focusses on accelerating development of drugs and drug combinations (antibiotics, host-directed therapies) systematically by including the immune system and influence of infection and inflammation in infectious and other diseases. To that aim, translationally predictive models such as PKPD, quantitative systems pharmacology (QSP) and physiology-based PK (PBPK) models are developed and applied to improve clinical efficacy predictions (e.g. tuberculosis and non-tuberculous mycobacterial infections). In concert with model development, Van Wijk’s research group has a semi-automated zebrafish pharmacology laboratory. The zebrafish is a phylogenetically lower vertebrate, positioned as new approach methodology (NAM) to mammalian in vivo experiments, and facilitates higher-throughput experimental data in a learn-and-confirm cycle with modelling, while remaining predictive to clinical efficacy.
Presentation: Predictive modelling to accelerate drug development in infectious diseases using the zebrafish as new approach methodology (NAM)
Accelerating development of drug (combinations) against infectious diseases is a global priority. Cases of mycobacterial infections, such as tuberculosis (TB) and non-tuberculous mycobacterial (NTM) infections are stationary or even rising nationally and globally [1-3]. These infections are especially hard to treat, requiring extensive treatment durations with multiple antibiotics. Translational predictive models, predicting clinical efficacy (or lack thereof) for drug combinations have been successfully developed based on rodent and rabbit in vivo data [4-6]. At the same time, new approach methodologies (NAM) to mammalian in vivo experiments are necessary [7]. One example of NAM is the lower phylogenetically vertebrate zebrafish (Danio rerio), combined with predictive pharmacokinetic-pharmacodynamic (PKPD) modelling [8]. The zebrafish embryo/larva is optically transparent allowing for longitudinal, microscopy-based quantification of for example fluorescent pathogens during disease progression and treatment [9]. Benefiting from lessons-learnt in mammalian predictive models, we have successfully quantified both PK and PD in the zebrafish mycobacterial infection model and successfully predicted clinical efficacy in several phase 2a trials of cornerstone antibiotics isoniazid and bedaquiline. With recent possibilities of automation through robotics, the zebrafish NAM model supported by PKPD modelling, will improve our understanding of drug efficacy and exposure earlier, accelerating and de-risking development of the most promising therapeutics.
[1] World Health Organization Global tuberculosis report 2025. (Geneva, 2025); [2] RIVM, Kerncijfers tuberculose (2025); [3] Lange et al, Pathog Immun 10(2) (2025); [4] Ernest et al, Eur Respir J 62, 2300165 (2023); [5] Ernest et al, Nat Comm eprint (2026); [6] Strydom et al, Sci Transl Med 17, eadi4000 (2025); [7] U.S. Department of Health and Human Service, Food and Drug Administration Web announcement: FDA releases draft guidance alternatives animal testing drug development (2026); [8] Forn-Cuní et al, bioRxiv 10.64898/2026.05.29.728504v1 (2026); [9] Van Wijk et al Br J Pharmacol 177, 5518–5533 (2020)
[1] World Health Organization Global tuberculosis report 2025. (Geneva, 2025); [2] RIVM, Kerncijfers tuberculose (2025); [3] Lange et al, Pathog Immun 10(2) (2025); [4] Ernest et al, Eur Respir J 62, 2300165 (2023); [5] Ernest et al, Nat Comm eprint (2026); [6] Strydom et al, Sci Transl Med 17, eadi4000 (2025); [7] U.S. Department of Health and Human Service, Food and Drug Administration Web announcement: FDA releases draft guidance alternatives animal testing drug development (2026); [8] Forn-Cuní et al, bioRxiv 10.64898/2026.05.29.728504v1 (2026); [9] Van Wijk et al Br J Pharmacol 177, 5518–5533 (2020)
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