26 papers · ranked by Valyu relevance
Anaïs Andrillon, Sandrine Micallef, Moreno Ursino, Pavel Mozgunov + 1 more
- A. Andrillon (1,2), S. Micallef (3), M. Ursino (4), P. Mozgunov (5), M-K Riviere (1) - 1) Department of Statistical Methodology, SARYGA, France - 2) INSERM U1153 Team ECSTRRA, Universit´e Paris Cit´e, Paris, France - 3) Debiopharm International SA, Lausanne, Switzerland - 4) HeKA, INSERM, Inria, Universit´e Paris…
Freya Bachmann, Gilbert Koch, Marc Pfister, Gabor Szinnai + 1 more
'Johannes Schropp'] Providing the optimal dosing strategy of a drug for an individual patient is an important task in pharmaceutical sciences and daily clinical application. We developed and validated an optimal dosing algorithm (OptiDose) that computes the optimal individualized dosing regimen for…
Wencel Valega-Mackenzie, Marisabel Rodriguez Messan, Osman N. Yogurtcu, Ujwani Nukala + 2 more
The advancements in next-generation sequencing have made it possible to effectively detect somatic mutations, which has led to the development of personalized neoantigen cancer vaccines that are tailored to the unique variants found in a patient’s cancer. These vaccines can provide significant clinical benefit by…
Martin Dodek, Zuzana Vitková, Anton Vitko, Eva Miklovičová + 1 more
Oral drug therapy requires achieving a delicate balance between therapeutic efficacy and patient safety, yet current dosing strategies often rely on empirical trial-and-error methods that overlook the complex nonlinear dynamic nature of drug behavior in the human body. Conventional pharmacokinetic/pharmacodynamic…
S. Mahmoodifar, P.K. Newton
We introduce a mathematical model of the cancer-immunity cycle and use it to test several hypotheses regarding the combination, timing, and optimization associated with chemotherapy and immunotherapy dosing schedules in the context of competition and selection pressure. A key conceptual idea is the value of…
Freya Bachmann, Gilbert Koch, Robert J. Bauer, Britta Steffens + 3 more
'Gabor Szinnai' 'Marc Pfister' 'Johannes Schropp'] Recently, an optimal dosing algorithm (OptiDose) was developed to compute the optimal drug doses for any pharmacometrics model for a given dosing scenario. In the present work, we enhance the OptiDose concept to compute optimal drug dosing with respect to both efficacy…
Xin Chen, Ruyue He, Xinyi Chen, Liyun Jiang + 1 more
Due to the small sample sizes in early-phase clinical trials, the toxicity and efficacy profiles of the dose-schedule regimens determined for subsequent trials may not be well established. The recent development of novel anti-tumor treatments and combination therapies further complicates the problem. Therefore, there…
Ayush Garg, Shyam Sundar Das, Naveen Sivadasan, Arijit Roy + 1 more
Optimizing dose and schedule remains a central challenge in oncology drug development, particularly for immunotherapies where fixed dosing regimens often fail to account for patient specific heterogeneity in tumor–immune dynamics. Here, we present a hybrid quantitative systems pharmacology–reinforcement learning–Monte…
Rachel J. Tyson, Christine C. Park, J. Robert Powell, J. Herbert Patterson + 3 more
'J. Herbert Patterson' 'Daniel Weiner' 'Paul B. Watkins' 'Daniel Gonzalez'] The administered dose of a drug modulates whether patients will experience optimal effectiveness, toxicity including death, or no effect at all. Dosing is particularly important for diseases and/or drugs where the drug can decrease severe…
James M. Willard, Shirin Golchi, Erica E. M. Moodie, Bruno Boulanger + 1 more
'Bradley P. Carlin'] Identification of optimal dose combinations in early phase dose-finding trials is challenging, due to the trade-off between precisely estimating the many parameters required to flexibly model the possibly non-monotonic dose-response surface, and the small sample sizes in early phase trials. This…
Chris Rackauckas, Vaibhav Dixit, Adam R. Gerlach, Vijay Ivaturi
Personalized precision dosing is about mathematically determining effective dosing strategies that optimize the probability of containing a patient’s outcome within a therapeutic window. However, the common Monte Carlo approach for generating patient statistics is computationally expensive because thousands of…
Steven Piantadosi, Guohai Zhou
We present a flexible and general adaptive experimental design for dose finding clinical trials. This method can be applied in sterotypical settings such as determining a maximum tolerated dose, when the dose response relationship is complex, or when the response is an arbitrary quantitative measure. Our design…
J. Willard, Shirin Golchi, Erica E. M. Moodie
Combinations in Personalized Dose-Finding Trials Authors: ['J. Willard' 'Shirin Golchi' 'Erica E. M. Moodie'] Early phase, personalized dose-finding trials for combination therapies seek to identify patientspecific optimal biological dose (OBD) combinations, which are defined as safe dose combinations which maximize…
Peng Yang, Daniel Li, Ruitao Lin, Bo Huang + 1 more
The conventional more-is-better dose selection paradigm, which targets the maximum tolerated dose (MTD), is not suitable for the development of targeted therapies and immunotherapies as the efficacy of these novel therapies may not increase with the dose. The U.S. Food and Drug Administration (FDA) has launched Project…
Zhenghao Jiang, Gu Mi, Lin Ji, Christelle Lorenzato + 1 more
The Project Optimus initiative by the FDA's Oncology Center of Excellence is widely viewed as a groundbreaking effort to change the status quo of conventional dose-finding strategies in oncology. Unlike in other therapeutic areas where multiple doses are evaluated thoroughly in dose ranging studies, early-phase…
Guy Katriel
This work studies fundamental questions regarding the optimal design of antimicrobial treatment protocols, using pharmacodynamic and pharmacokinetic mathematical models. We consider the problem of designing an antimicrobial treatment schedule to achieve eradication of a microbial infection, while minimizing the area…
Solveig A. van der Vegt, Ruth E. Baker, Sarah L. Waters
Autoimmune myocarditis, or cardiac muscle inflammation, is a rare but frequently fatal side–effect of immune checkpoint inhibitors (ICIs), a class of cancer therapies. Despite the dangers that side-effects such as these pose to patients, they are rarely, if ever, included explicitly when mechanistic mathematical…
Eric Vermeulen, John N. van den Anker, Oscar Della Pasqua, Kalle Hoppu + 1 more
Dose-ranging studies, also known as phase II studies, occupy a key position in clinical drug development. If properly designed and accurately performed, a dose-finding study will save time and effort during the assessment of efficacy in comparative and large-scale trials in phase III. Moreover, evidence from these…
Maral Budak, Joseph M. Cicchese, Pauline Maiello, H. Jacob Borish + 13 more
Tuberculosis (TB) continues to be one of the deadliest infectious diseases in the world, causing ~1.5 million deaths every year. The World Health Organization initiated an End TB Strategy that aims to reduce TB-related deaths in 2035 by 95%. Recent research goals have focused on discovering more effective and more…
Authors not listed
Therapeutic drug monitoring enables personalized cancer medicine by dosing patients with chemotherapy based on the patient’s own unique rate of drug clearance and metabolic degradation. These rates significantly influence the plasma concentration which influences patient outcomes. This is especially true for the…
Authors not listed
S-892216 is a poorly water-soluble drug developed as a novel oral treatment of COVID-19, although its oral absorption is low. For Phase 1 (Ph1) studies and commercial use, both oral solution and solid dispersion technologies are evaluated to enhance drug solubility. The solubility enhancement technology was selected by…
Corinna Schlosser, Wojciech Rozek, Ryan Mellor, Szymon Manka + 3 more
Teriparatide (and analogue peptides) are the only FDA approved anabolic treatments for osteoporosis. Current therapies are administered as a daily subcutaneous injection, which limits patient adherence and clinical efficacy. To achieve the desired anabolic effect, a controlled delivery system must ensure a pulsatile…
Pablo Quijano Velasco, Kedar Hippalgaonkar, Balamurugan Ramalingam
The discovery of optimal conditions of chemical reactions is a labor-intensive, time-consuming task that requires exploring a high-dimensional parametric space. Historically the optimization of chemical reactions has been performed by manual experimentation guided by human intuition and Design of Experiments where one…
Riley Hickman, Priyansh Parakh, Austin Cheng, Qianxiang Ai + 3 more
Experiment planning algorithms are a required component of autonomous platforms for scientific discovery. Selecting a suitable optimization algorithm for a novel application is an important yet difficult choice a researcher has to make based on past empirical performance on similar tasks. To facilitate the evaluation…
Riley Hickman, Matteo Aldeghi, Alán Aspuru-Guzik
Model-based optimization strategies, such as Bayesian optimization (BO), have been deployed across the natural sciences in design and discovery campaigns due to their sample efficiency and flexibility. The combination of such strategies with automated laboratory equipment and/or high-performance computing in a…
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This article presents an overview about the state of the art in the development of structured packings for distillation applications. The focus is on highlighting different approaches including heuristic development cycles, the development of new packing structures, 3D-printing as tool for manufacturing, and…