Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Jaimit Parikh"'
Publikováno v:
Royal Society Open Science, Vol 10, Iss 11 (2023)
Predictions for physical systems often rely upon knowledge acquired from ensembles of entities, e.g. ensembles of cells in biological sciences. For qualitative and quantitative analysis, these ensembles are simulated with parametric families of mecha
Externí odkaz:
https://doaj.org/article/2609bf6acf2440b4822f9f0c103815cc
Publikováno v:
iScience, Vol 24, Iss 11, Pp 103279- (2021)
Summary: Preclinical drug candidates are screened for their ability to ameliorate in vitro neuronal electrophysiology, and go/no-go decisions progress drugs to clinical trials based on population means across cells and animals. However, these measure
Externí odkaz:
https://doaj.org/article/1c7b6625b6fe493881da67d82223dbf5
Autor:
Paolo Di Achille, Jaimit Parikh, Svyatoslav Khamzin, Olga Solovyova, James Kozloski, Viatcheslav Gurev
Publikováno v:
PLoS ONE, Vol 15, Iss 1, p e0219876 (2020)
Computational models of the cardiovascular system and specifically heart function are currently being investigated as analytic tools to assist medical practice and clinical trials. To achieve clinical utility, models should be able to assimilate the
Externí odkaz:
https://doaj.org/article/e9ded6c683274eac96fd56a609912d36
Publikováno v:
Frontiers in Pharmacology, Vol 10 (2019)
Multiscale computational models of the heart are being extensively investigated for improved assessment of drug-induced torsades de pointes (TdP) risk, a fatal side effect of many drugs. Model-derived metrics such as action potential duration and net
Externí odkaz:
https://doaj.org/article/08a42291412d4bae9ff2140d674f32c2
Publikováno v:
Frontiers in Pharmacology, Vol 8 (2017)
While pre-clinical Torsades de Pointes (TdP) risk classifiers had initially been based on drug-induced block of hERG potassium channels, it is now well established that improved risk prediction can be achieved by considering block of non-hERG ion cha
Externí odkaz:
https://doaj.org/article/1fe8356584fd43e095b197dc51dc0ee4
Autor:
Tongli, Zhang, Ioannis P, Androulakis, Peter, Bonate, Limei, Cheng, Tomáš, Helikar, Jaimit, Parikh, Christopher, Rackauckas, Kalyanasundaram, Subramanian, Carolyn R, Cho
Publikováno v:
Journal of Pharmacokinetics and Pharmacodynamics. 49:5-18
Quantitative systems pharmacology (QSP) modeling is applied to address essential questions in drug development, such as the mechanism of action of a therapeutic agent and the progression of disease. Meanwhile, machine learning (ML) approaches also co
Autor:
Jaimit Parikh, Anastasia Khokhlova, Viatcheslav Gurev, Timothy Rumbell, Xenia Butova, Tatiana Myachina, Jorge Corral Acero, Svyatoslav Khamzin, Olga Solovyova, James R. Kozloski
Publikováno v:
J. Pharmacokinet. Pharmacodyn.
Journal of Pharmacokinetics and Pharmacodynamics
OpenAIRE
Microsoft Academic Graph
Journal of Pharmacokinetics and Pharmacodynamics
OpenAIRE
Microsoft Academic Graph
Biophysical models are increasingly used to gain mechanistic insights by fitting and reproducing experimental and clinical data. The inherent variability in the recorded datasets, however, presents a key challenge. In this study, we present a novel a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::30e4b7a82b29053b5845b78470e1713f
https://hdl.handle.net/10995/111333
https://hdl.handle.net/10995/111333
Autor:
Hitesh Mistry, Jaimit Parikh
There has been a lot of interest and publicity regarding the use of a complex biophysical model within drug development for predicting the TdeP risk of new compounds. Throughout the development of the complex model numerous groups have shown that a s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::da28ca3603d9fad9d13675a73f671037
https://doi.org/10.1101/2020.06.11.144238
https://doi.org/10.1101/2020.06.11.144238
Autor:
Hitesh Mistry, Jaimit Parikh
Publikováno v:
Journal of Pharmacological and Toxicological Methods. 111:107049
Publikováno v:
American Journal of Physiology-Heart and Circulatory Physiology. 312:H854-H866
We used mathematical modeling to investigate nitric oxide (NO)-dependent vasodilatory signaling in the arteriolar wall. Detailed continuum cellular models of calcium (Ca2+) dynamics and membrane electrophysiology in smooth muscle and endothelial cell