Improving Realism in Clinical Trial Simulations via Real-World Data

Interdisciplinary Collaboration on Real World Data to Close the Knowledge Gap: A Reflection on "De Sutter et al. Predicting Volume of Distribution in Neonates: Performance of Physiologically Based Pharmacokinetic Modelling"

This commentary further reflects on the paper of De Sutter et al. on predicting volume of distribution in neonates, and the performance of physiologically based pharmacokinetic models We hereby stressed the add on value to collaborate on real world data to further close this knowledge gap. We illustrated this by weight distribution characteristics in breastfed (physiology) and in asphyxiated (pathophysiology), with additional reflection on their kidney and liver function.

Current and future physiologically based pharmacokinetic (PBPK) modeling approaches to optimize pharmacotherapy in preterm neonates

INTRODUCTION

There is a need for structured approaches to inform on pharmacotherapy in preterm neonates. With their proven track record up to regulatory acceptance, physiologically based pharmacokinetic (PBPK) modeling and simulation provide such a structured approach, and hold the promise to support drug development in preterm neonates.

AREAS COVERED

Compared to the general and pediatric use of PBPK modeling, its use to inform pharmacotherapy in preterms is limited. Using a systematic search (PBPK + preterm), we retained 25 records (20 research papers, 2 letters, 3 abstracts). We subsequently collated the published information on PBPK software packages (PK-Sim®, Simcyp®), and their applications and optimization efforts in preterm neonates. It is encouraging that these applications cover a broad range of scenarios (pharmacokinetic-dynamic analyses, drug-drug interactions, developmental pharmacogenetics, lactation related exposure) and compounds (small molecules, proteins). Furthermore, specific compartments (cerebrospinal fluid, tissue) or (patho)physiologic processes (cardiac output, biliary excretion, first pass metabolism) are considered.

EXPERT OPINION

Knowledge gaps exist, giving rise to various levels of model uncertainty in PBPK applications in preterm neonates. To improve this setting, we need cross talk between clinicians and modelers to generate and integrate knowledge (PK datasets, system knowledge, maturational physiology and pathophysiology) to further refine PBPK models.

Simulating Colorectal Cancer Trials Using Real-World Data

PURPOSE

Using real-world data (RWD)-based trial simulation approach, we aim to simulate colorectal cancer (CRC) trials and examine both effectiveness and safety end points in different simulation scenarios.

METHODS

We identified five phase III trials comparing new treatment regimens with an US Food and Drug Administration-approved first-line treatment in patients with metastatic CRC (ie, fluorouracil, leucovorin, and irinotecan) as the standard-of-care (SOC) control arm. Using Electronic Health Record-derived data from the OneFlorida network, we defined the study populations and outcome measures using the protocols from the original trials. Our design scenarios were (1) simulation of the SOC fluorouracil, leucovorin, and irinotecan arm and (2) comparative effectiveness research (CER) simulation of the control and experimental arms. For each scenario, we adjusted for random assignment, sampling, and dropout. We used overall survival (OS) and severe adverse events (SAEs) to measure effectiveness and safety.

RESULTS

We conducted CER simulations for two trials, and SOC simulations for three trials. The effect sizes of our simulated trials were stable across all simulation runs. Compared with the original trials, we observed longer OS and higher mean number of SAEs in both CER and SOC simulation. In the two CER simulations, hazard ratios associated with death from simulations were similar to that reported in the original trials. Consistent with the original trials, we found higher risk ratios of SAEs in the experiment arm, suggesting potentially higher toxicities from the new treatment regimen. We also observed similar SAE rates across all simulations compared with the original trials.

CONCLUSION

In this study, we simulated five CRC trials, and tested two simulation scenarios with several different configurations demonstrated that our simulations can robustly generate effectiveness and safety outcomes comparable with the original trials using real-world data.

Pharmacokinetic/pharmacodynamic evaluation of tobramycin dosing in critically ill patients: the Hartford nomogram does not fit

OBJECTIVES

Extended-interval dosing of tobramycin is widely applied in patients with the Hartford nomogram as a representative, while this dosing approach has not been extensively evaluated in critically ill patients. The goal of this study was to characterize the pharmacokinetics of tobramycin and to evaluate the appropriateness of the Hartford nomogram in critically ill patients.

METHODS

A retrospective analysis was performed based on a medical critical care database. The extracted concentration data of tobramycin were used for the construction of the population pharmacokinetic model using a non-linear mixed-effects modelling approach. Real-world data-based simulations were conducted to evaluate the pharmacodynamic target attainment (Cmax/MIC ≥10) and safety (concentration <0.5 mg/L for at least 4 h) of the Hartford nomogram.

RESULTS

A population pharmacokinetic model was built based on 307 measurements in 140 unique patients and externally validated by an independent study dataset. A two-compartment model was optimal for the structure model and creatinine clearance remained as the only covariate in the final model correlating to the clearance of tobramycin. Simulations indicated that the Hartford nomogram is effective for infections due to pathogens with an MIC of ≤1 mg/L, but not with an MIC of 2 mg/L. The percentage of patients who reached the non-toxicity target was quite low under the Hartford nomogram and a further extension of the dosing interval was necessary to minimize the toxicity.

CONCLUSIONS

The Hartford nomogram was not suitable for critically ill patients with pathogen MICs of 2 mg/L and drug monitoring is required to manage efficacy and toxicity.

Ontogeny of Phase I Metabolism of Drugs

Capturing ontogeny of enzymes involved in phase I metabolism is crucial to improve prediction of dose-concentration and concentration-effect relationships throughout infancy and childhood. Once captured, these patterns can be integrated in semiphysiologically or physiology-based pharmacokinetic models to support predictions in specific pediatric settings or to support pediatric drug development. Although these translational efforts are crucial, isoenzyme-specific ontogeny-based models should also incorporate data on variability of maturational and nonmaturational covariates (eg, disease, treatment modalities, pharmacogenetics). Therefore, this review provides a summary of the ontogeny of phase I drug-metabolizing enzymes, indicating current knowledge gaps and recent progresses. Furthermore, we tried to illustrate that straightforward translation of isoenzyme-specific ontogeny to predictions does not allow full exploration of scenarios of potential variability related to maturational (non-age-related variability, other isoenzymes or transporters) or nonmaturational (disease, pharmacogenetics) covariates, and necessitates integration in a "systems" concept.

Clinical trial simulations of the interaction between cannabidiol and clobazam and effect on drop-seizure frequency

With this study, we aim to test the hypothesis that the effect of cannabidiol on drop-seizure frequency in patients with Lennox-Gastaut syndrome and Dravet syndrome could be attributed to a drug-drug interaction with clobazam. We performed clinical trial simulations for the effect of 20 mg/kg/day cannabidiol on drop-seizure frequency in patients with Lennox-Gastaut syndrome. We assumed that patients taking 10 or 20 mg clobazam would have a 2- to 7-fold increase in N-desmethylclobazam exposure, whereas patients not taking clobazam would have a median reduction in drop-seizure frequency and a variability in the percent reduction similar to the placebo group. The results show that the effect of cannabidiol on the median reduction in drop-seizure frequency in patients with Lennox-Gastaut syndrome may be explained by a drug-drug interaction with clobazam. This may have important implications for the use of cannabidiol and its Food and Drug Administration registration.

Physiologically based pharmacokinetic (PBPK) modeling and simulation in neonatal drug development: how clinicians can contribute

Introduction: Legal initiatives to stimulate neonatal drug development should be accompanied by development of valid research tools. Physiologically based (PB)-pharmacokinetic (PK) modeling and simulation are established tools, accepted by regulatory authorities. Consequently, PBPK holds promise to be a strong research tool to support neonatal drug development. Area covered: The currently available PBPK models still have poor predictive performance in neonates. Using an illustrative approach on distinct PK processes of absorption, distribution, metabolism, excretion, and real-world data in neonates, we provide evidence on the need to further refine available PBPK system parameters through generation and integration of new knowledge. This necessitates cross talk between clinicians and modelers to integrate knowledge (PK datasets, system knowledge, maturational physiology) or test and refine PBPK models. Expert opinion: Besides refining these models for 'small molecules', PBPK model development should also be more widely applied for therapeutic proteins and to determine exposure through breastfeeding. Researchers should also be aware that PBPK modeling in combination with clinical observations can also be used to elucidate age-related changes that are almost impossible to study based on in vivo or in vitro data. This approach has been explored for hepatic biliary excretion, renal tubular activity, and central nervous system exposure.