Biology subjects

van Wijk, R. C.

Publications and source records attributed to van Wijk, R. C..

3 recordsLinked to original sources

bioRxiv2026

Predicting tuberculosis relapse based on 28-day CFU, RS ratio, and/or drug contribution for novel regimens in the relapsing mouse model

Treatment shortening in tuberculosis therapy is needed, but testing all novel antibiotic combinations is unfeasible. Especially the tuberculosis relapsing mouse model is time- and resource demanding. Therefore, our objective is to develop a computational model predictive of long-term relapse prevention in mice based on short-term biomarkers, increasing the number of regimens that can be tested and prioritize regimens for further development. The innovative ribosomal RNA synthesis (RS) ratio is utilized to characterize drug effect on Mycobacterium tuberculosis health and activity, together with colony forming units (CFU) in murine lungs. Nine datasets of 58 unique regimens with 843 short-term biomarker and 2,239 long-term relapse observations were leveraged for model development in 3 iterations with external validations. The final model included therapeutic predictors, such as CFU and RS ratio change from baseline, and corrected for experimental conditions, to enable unbiased ranking of regimens between experiments. Model performance was optimal without model structure change despite fully separate model development at each iteration. Final external validation had an area under the receiver operator curve of 0.90. Challenging the model by assessing removal of either biomarker showed that performance of CFU only was similar to CFU and RS ratio once the sterilizing contribution of individual drugs to the regimens was accounted for. New drugs without this contribution quantified could benefit from RS ratio determination to predict relapse. Our predictive model can successfully differentiate between 2-, 3-, and 4-month regimens in the relapsing mouse model based on 4-week data only, supporting acceleration of treatment-shortening regimen development. One Sentence SummaryOur predictive model ranks new drug regimens by tuberculosis relapse prevention based on 28-day CFU and RS ratio, or on CFU only for known drugs.

pharmacology and toxicology↗

bioRxiv2026

Accelerating drug development in infectious diseases using zebrafish disease models supported by pharmacokinetic pharmacodynamic modeling as new approach methodology (NAM)

The development of novel therapeutics for infectious diseases remains a global health priority. To accelerate the treatment development, innovative strategies through new approach methodology (NAM) are needed to bridge speed of in vitro with predictive power of in vivo studies, while reducing mammalian experiments. The zebrafish (Danio rerio), particularly the embryo/larva, has been established as a valuable non-mammalian in vivo model in biomedical research. We developed a standardized and streamlined workflow for the zebrafish as NAM, which consisted of 3 steps: drug selection and efficacy evaluation, internal exposure assessment, and PKPD modelling. Compounds with higher tolerated doses than minimum inhibitory concentration were selected. Drug efficacy was quantified through longitudinal individual fluorescence microscopy at baseline and 24 and 48h on treatment. Drug exposure was quantified in larval homogenates and exposure medium from 0-48h on treatment. The PKPD relationship was quantified by non-linear mixed effects modelling. For case study bedaquiline, PKPD was quantified using a one-compartment model with age-depending elimination, and an Emax concentration-response relationship on the delayed logistic bacterial growth function, with an EC50 of 26.6 {micro}g/mL and an Emax of 1.07-1.37. In the case of clarithromycin, in contrast, negligible internal exposure after waterborne treatment were observed, illustrating the risk of false negatives without internal exposure assessments. Bactericidal efficacy was confirmed by intravenous drug injections, showing a clear dose dependent antimycobacterial effect. The standardized zebrafish NAM workflow presented here facilitates the translation of drug efficacy to higher vertebrates, reducing rodent studies to confirmatory or replacing them completely, thus accelerating drug development.

pharmacology and toxicology↗

bioRxiv2023

Translational predictions of phase 2a first-in patient efficacy studies for antituberculosis drugs

BackgroundPhase 2a trials in tuberculosis typically use early bactericidal activity (EBA), the decline in sputum colony forming units (CFU) over 14 days, as the primary outcome for testing the efficacy of drugs as monotherapy. However, the cost of phase 2a trials can range from 7 to 19.6 million dollars on average, while more than 30% of drugs fail to progress to phase 3. Better utilizing preclinical data to predict and prioritize the most likely drugs to succeed will thus help accelerate drug development and reduce costs. We aim to predict clinical EBA using preclinical in vivo pharmacokinetic-pharmacodynamic (PKPD) data and a model-based translational pharmacology approach. Methods and FindingsFirst, mouse PK, PD and clinical PK models were compiled. Second, mouse PKPD models were built to derive an exposure response relationship. Third, translational prediction of clinical EBA studies was performed using mouse PKPD relationships and informed by clinical PK models and species-specific protein binding. Presence or absence of clinical efficacy was accurately predicted from the mouse model. Predicted daily decreases of CFU in the first 2 days of treatment and between day 2 and day 14 were consistent with clinical observations. ConclusionThis platform provides an innovative solution to inform or even replace phase 2a EBA trials, to bridge the gap between mouse efficacy studies and phase 2b and phase 3 trials, and to substantially accelerate drug development.

pharmacology and toxicology↗