Papers by Kumpal Madrasi, Ph.D.
Blood, Nov 27, 2023
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Pharmaceutics, Jul 7, 2016
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CPT: pharmacometrics & systems pharmacology, Nov 1, 2014
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IFAC-PapersOnLine, 2022
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Alzheimers & Dementia, Jul 1, 2019
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Nitric Oxide, May 1, 2011
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The Journal of Clinical Pharmacology, Dec 1, 2020
Costly and lengthy clinical trials hinder the development of safe and effective treatments for po... more Costly and lengthy clinical trials hinder the development of safe and effective treatments for postmenopausal osteoporosis. To reduce the expense associated with these trials, we established a mechanistic disease‐drug trial model for postmenopausal osteoporosis that can predict phase 3 trial outcome based on short‐term bone turnover marker data. To this end, we applied a previously developed model for tibolone to bisphosphonates using zoledronic acid as paradigm compound by (1) linking the mechanistic bone cell interaction model to bone turnover markers as well as bone mineral density in lumbar spine and total hip, (2) employing a mechanistic disease progression function, and (3) accounting for zoledronic acid's mechanism of action. Once developed, we fitted the model to clinical trial data of 581 postmenopausal women receiving (1) 5‐mg zoledronic acid in year 1 and saline in year 2, (2) 5‐mg zoledronic acid in year 1 and year 2, or (3) placebo (saline), calcium (500 mg), and vitamin D (400 IU). All biomarker data was fitted reasonably well, with no apparent bias or model misspecification. Age, years since menopause, and body mass index at baseline were identified as significant covariates. In the future, the model can be modified to explore the link between short‐term biomarkers and fracture risk.
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The FASEB Journal, Apr 1, 2010
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Clinical Pharmacology & Therapeutics
Recent breakthroughs in artificial intelligence (AI) and machine learning (ML) have ushered in a ... more Recent breakthroughs in artificial intelligence (AI) and machine learning (ML) have ushered in a new era of possibilities across various scientific domains. One area where these advancements hold significant promise is model‐informed drug discovery and development (MID3). To foster a wider adoption and acceptance of these advanced algorithms, the Innovation and Quality (IQ) Consortium initiated the AI/ML working group in 2021 with the aim of promoting their acceptance among the broader scientific community as well as by regulatory agencies. By drawing insights from workshops organized by the working group and attended by key stakeholders across the biopharma industry, academia, and regulatory agencies, this white paper provides a perspective from the IQ Consortium. The range of applications covered in this white paper encompass the following thematic topics: (i) AI/ML‐enabled Analytics for Pharmacometrics and Quantitative Systems Pharmacology (QSP) Workflows; (ii) Explainable Artifi...
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The Journal of Clinical Pharmacology, Dec 6, 2016
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CPT: Pharmacometrics & Systems Pharmacology
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IFAC-PapersOnLine
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The FASEB Journal, Apr 1, 2011
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The FASEB Journal, 2013
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The FASEB Journal, 2012
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The FASEB Journal, 2010
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The Journal of Clinical Pharmacology, 2020
Costly and lengthy clinical trials hinder the development of safe and effective treatments for po... more Costly and lengthy clinical trials hinder the development of safe and effective treatments for postmenopausal osteoporosis. To reduce the expense associated with these trials, we established a mechanistic disease‐drug trial model for postmenopausal osteoporosis that can predict phase 3 trial outcome based on short‐term bone turnover marker data. To this end, we applied a previously developed model for tibolone to bisphosphonates using zoledronic acid as paradigm compound by (1) linking the mechanistic bone cell interaction model to bone turnover markers as well as bone mineral density in lumbar spine and total hip, (2) employing a mechanistic disease progression function, and (3) accounting for zoledronic acid's mechanism of action. Once developed, we fitted the model to clinical trial data of 581 postmenopausal women receiving (1) 5‐mg zoledronic acid in year 1 and saline in year 2, (2) 5‐mg zoledronic acid in year 1 and year 2, or (3) placebo (saline), calcium (500 mg), and vitamin D (400 IU). All biomarker data was fitted reasonably well, with no apparent bias or model misspecification. Age, years since menopause, and body mass index at baseline were identified as significant covariates. In the future, the model can be modified to explore the link between short‐term biomarkers and fracture risk.
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The Journal of Clinical Pharmacology, 2019
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Alzheimer's & Dementia, 2019
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Papers by Kumpal Madrasi, Ph.D.