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Statistical Approaches in the Development of Digital Therapeutics
Published in Oleksandr Sverdlov, Joris van Dam, Digital Therapeutics, 2023
Oleksandr Sverdlov, Yevgen Ryeznik, Sergei Leonov, Valerii Fedorov
The field of digital therapeutics is not limited to mobile cognitive-behavioral interventions. Other indications will likely require different approaches to evidence generation. For instance, the artificial pancreas for type 1 diabetes relies on mathematical models describing the dynamics of physiological processes such as metabolite, glucose sensing, and insulin delivery. There are approaches to describe and analyze the dynamics given the measurements made by a device. Thus, pharmacometrics (PMx) will play an important role in modeling such a system and implementing it in real life. If a mathematical model of the process physiology is available, one can add a control term (treatment delivery) in the system. Then treatment delivery will be driven by the optimal control, determined as a mathematical solution to a corresponding control problem, e.g., keeping an insulin level within certain bounds over time. Some examples of utilizing control theory for drug delivery can be found, for instance, in Medvedev et al. (2019) and Johansson et al. (2018).
Biostatistics
Published in Arkadiy Pitman, Oleksandr Sverdlov, L. Bruce Pearce, Mathematical and Statistical Skills in the Biopharmaceutical Industry, 2019
Arkadiy Pitman, Oleksandr Sverdlov, L. Bruce Pearce
Finally, let us briefly discuss software whose existence should be recognized. One of the best biostatistician’s allies in the big pharma industry is the pharmacometrician [67]. This individual is an expert in PK/PD modeling and simulations and he/she plays a major role in model-based drug development. Pharmacometricians use their own set of tools which may be a puzzle for statisticians; for instance, the NONMEM (for NONlinear Mixed Effects Modeling) software, developed by Stuart Beal and Lewis Shiner at the University of California, San Francisco, in the late 1970’s. NONMEM is perhaps as important for pharmacometricians as SAS is for statisticians. It is very intricate and complex for non-specialists; yet it is a time-proven powerful tool to do modeling and simulations for calibration of dose/regimen schedules. Another useful and increasingly popular software for pharmacometrics is Monolix—http://lixoft.com/products/monolix/. Importantly, it has a free license for academic institutions.
A Regulatory View on Dose-Finding Studies and on the Value of Dose–Exposure–Response Analysis
Published in John O’Quigley, Alexia Iasonos, Björn Bornkamp, Handbook of Methods for Designing, Monitoring, and Analyzing Dose-Finding Trials, 2017
Sofia Friberg Hietala, Efthymios Manolis, Flora Musuamba Tshinanu
Pharmacometrics as applied in Model-Informed Drug Discovery and Development (MID3) (Marshall et al., 2015) offers a “quantitative framework for prediction and extrapolation, centered on knowledge and inference generated from integrated models of compound, mechanism, and disease level data, and aimed at improving the quality, efficiency, and cost effectiveness of decision making.” This approach differentiates from the two previously described by the possibility of including mechanistic thinking and translating physiological and pharmacological knowledge (and related uncertainties) into mathematical models. This is an important feature that allows filling the gap left by incomplete data and/or correcting the errors generated by poor-quality and uninformative studies.
Biopredictive tools for the development of injectable drug products
Published in Expert Opinion on Drug Delivery, 2022
Mônica Villa Nova, Kennard Gan, Matthias G. Wacker
The development of biopredictive performance assays requires preclinical or clinical in-vivo data to identify the rate-controlling elements in the absorption kinetics. The first steps involve a deconvolution of the pharmacokinetic profile to obtain the absorption rate. First described in the 1950s, pharmacometrics is a research area exploring the interactions between drug molecules and patients by developing suitable mathematical models [42]. Today, pharmacometric analysis and simulation are conducted using specific software. Although each software enables the analysis and integration of in-vivo data to a certain extent, there are significant differences in their application. Non-linear mixed effect (NLME) models are preferably used for the statistical analysis of patient data including individuals and populations. Physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) models further integrate physiological information such as tissue density and blood flow rate. They provide a detailed theoretical framework for each of these processes as well as the resulting in-vivo effects. However, as compared to NMLE models, knowledge gaps often lead to a disconnect between the predicted and the observed data. Suitable software that is commonly used in the development of biopredictive models has been summarized in Table 3.
Comparing the pharmacokinetics and organ/tissue distribution of anti-methicillin-resistant Staphylococcus aureus agents using a rat model of sepsis
Published in Xenobiotica, 2022
Shinji Kobuchi, Naoya Kanda, Taichi Okumi, Yuma Kano, Himawari Tachi, Yukako Ito, Toshiyuki Sakaeda
The results of pharmacokinetic evaluations showed that the alteration patterns in the distribution of anti-MRSA drugs to the organs/tissues under sepsis conditions were different for each drug. Considering the pharmacokinetic-pharmacodynamic theory, the dose setting for patients with sepsis should be determined based on the drug levels in the plasma and infection site. The pharmacometrics approach using a physiologically based pharmacokinetic model might be preferable to evaluate and compare the time-course profiles of drug concentration in organs/tissues under sepsis. The current data, including drug levels in plasma and organs/tissues in sepsis, can contribute to further analysis using the pharmacometrics approach. However, to obtain a desirable efficacy and escape antimicrobial resistance, further studies are required to elucidate the distribution of niche extravascular tissue spaces under sepsis conditions.
Reported needs of information resources, research tools, connectivity and infrastructure among African Pharmacological Scientists to improve future patient care and health
Published in Expert Review of Clinical Pharmacology, 2019
Olayinka O. Ogunleye, Joseph O. Fadare, Jaran Eriksen, Omo Oaiya, Amos Massele, Ilse Truter, Simon J.E. Taylor, Brian Godman, Lars L. Gustafsson
The expressed pharmacological science-based needs by the respondents have been met in part with the availability of pharmacokinetics and pharmacometrics resources. However, there is currently no specific availability of resources on Drug Utilization Research (DUR) which was the most frequently expressed area of need in this survey on the APSG platform. However, the recent instigation of the ISPE African chapter with access to a wide range of resources [59], and combined with the increased availability of training courses at MURIA workshops with all the materials available online afterwards are addressing these needs. The inclusion of DUR tools in the APSG e-infrastructure will further strengthen these efforts. Other key areas include issues of prices of medicines across SSA and internationally for comparative purposes as well as tools for assessing drug–drug interactions as expressed by respondents. These are considerations for the future.