Jagdeep T. Podichetty
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View article: How <scp>AI</scp> Transforms Regulatory Submission: Current Clinical Implementation and Future Prospects
How <span>AI</span> Transforms Regulatory Submission: Current Clinical Implementation and Future Prospects Open
Artificial Intelligence (AI) is transforming drug development and regulatory submission by enabling advanced data analytics, predictive modeling and intelligent decision support systems. Beyond efficiency gains, AI establishes a translatio…
View article: Unveiling sub-populations in critical care settings: a real-world data approach in COVID-19
Unveiling sub-populations in critical care settings: a real-world data approach in COVID-19 Open
Background Disease presentation and progression can vary greatly in heterogeneous diseases, such as COVID-19, with variability in patient outcomes, even within the hospital setting. This variability underscores the need for tailored treatm…
View article: AI‐Driven Applications in Clinical Pharmacology and Translational Science: Insights From the ASCPT 2024 AI Preconference
AI‐Driven Applications in Clinical Pharmacology and Translational Science: Insights From the ASCPT 2024 AI Preconference Open
Artificial intelligence (AI) is driving innovation in clinical pharmacology and translational science with tools to advance drug development, clinical trials, and patient care. This review summarizes the key takeaways from the AI preconfer…
View article: Wrangling Real-World Data: Optimizing Clinical Research Through Factor Selection with LASSO Regression
Wrangling Real-World Data: Optimizing Clinical Research Through Factor Selection with LASSO Regression Open
Data-driven approaches to clinical research are necessary for understanding and effectively treating infectious diseases. However, challenges such as issues with data validity, lack of collaboration, and difficult-to-treat infectious disea…
View article: A Tutorial and Use Case Example of the <scp>eXtreme</scp> Gradient Boosting (<scp>XGBoost</scp>) Artificial Intelligence Algorithm for Drug Development Applications
A Tutorial and Use Case Example of the <span>eXtreme</span> Gradient Boosting (<span>XGBoost</span>) Artificial Intelligence Algorithm for Drug Development Applications Open
Approaches to artificial intelligence and machine learning (AI/ML) continue to advance in the field of drug development. A sound understanding of the underlying concepts and guiding principles of AI/ML implementation is a prerequisite to i…
View article: Real‐world evidence in the cloud: Tutorial on developing an end‐to‐end data and analytics pipeline using Amazon Web Services resources
Real‐world evidence in the cloud: Tutorial on developing an end‐to‐end data and analytics pipeline using Amazon Web Services resources Open
In the rapidly evolving landscape of healthcare and drug development, the ability to efficiently collect, process, and analyze large volumes of real‐world data (RWD) is critical for advancing drug development. This article provides a bluep…
View article: Type 1 diabetes prevention clinical trial simulator: Case reports of model‐informed drug development tool
Type 1 diabetes prevention clinical trial simulator: Case reports of model‐informed drug development tool Open
Clinical trials seeking to delay or prevent the onset of type 1 diabetes (T1D) face a series of pragmatic challenges. Despite more than 100 years since the discovery of insulin, teplizumab remains the only FDA‐approved therapy to delay pro…
View article: Accelerating healthcare innovation: the role of Artificial intelligence and digital health technologies in critical path institute’s public‐private partnerships
Accelerating healthcare innovation: the role of Artificial intelligence and digital health technologies in critical path institute’s public‐private partnerships Open
Artificial Intelligence (AI) and Digital Health Technologies (DHTs) are radically transforming drug development. The FDA and EMA have formulated guidance documents for their use in clinical trials. A pressing need exists for a harmonized a…
View article: Unlocking the Capabilities of Large Language Models for Accelerating Drug Development
Unlocking the Capabilities of Large Language Models for Accelerating Drug Development Open
Recent breakthroughs in natural language processing (NLP), particularly in large language models (LLMs), offer substantial advantages in model-informed drug development (MIDD). With billions of parameters and comprehensive pre-training on …
View article: Publication Recommendations to Report Laboratory Data of Neonates – a Modified Delphi Approach
Publication Recommendations to Report Laboratory Data of Neonates – a Modified Delphi Approach Open
Background Clinical and analytical information on laboratory data of neonates in scientific publications is sparse and incomplete. Furthermore, interpreting neonatal laboratory data can be complex due to their time-dependent and developmen…
View article: Extracting Lab Value Reference Ranges from Neonatal Real-World Data in OMOP Format
Extracting Lab Value Reference Ranges from Neonatal Real-World Data in OMOP Format Open
View article: A Bayesian Model-based CTS Tool to Optimize Clinical Trial Design in Duchenne Muscular Dystrophy
A Bayesian Model-based CTS Tool to Optimize Clinical Trial Design in Duchenne Muscular Dystrophy Open
View article: Optimizing Drug Development: Assessing Small Language Models for Efficient Drug-Drug Interaction Data Extraction
Optimizing Drug Development: Assessing Small Language Models for Efficient Drug-Drug Interaction Data Extraction Open
View article: Qualifying a Novel Clinical Trial Endpoint (iBOX) Predictive of Long-Term Kidney Transplant Outcomes
Qualifying a Novel Clinical Trial Endpoint (iBOX) Predictive of Long-Term Kidney Transplant Outcomes Open
New immunosuppressive therapies that improve long-term graft survival are needed in kidney transplant. Critical Path Institute’s Transplant Therapeutics Consortium received a qualification opinion for the iBOX Scoring System as a novel sec…
View article: Qualifying a novel clinical trial endpoint (iBOX) predictive of long-term kidney transplant outcomes
Qualifying a novel clinical trial endpoint (iBOX) predictive of long-term kidney transplant outcomes Open
New immunosuppressive therapies that improve long-term graft survival are needed in kidney transplant. Critical Path Institute's Transplant Therapeutics Consortium received a qualification opinion for the iBOX Scoring System as a novel sec…
View article: Disease progression joint model predicts time to type 1 diabetes onset: Optimizing future type 1 diabetes prevention studies
Disease progression joint model predicts time to type 1 diabetes onset: Optimizing future type 1 diabetes prevention studies Open
Clinical trials seeking type 1 diabetes prevention are challenging in terms of identifying patient populations likely to progress to type 1 diabetes within limited (i.e., short‐term) trial durations. Hence, we sought to improve such effort…
View article: How can natural language processing help model informed drug development?: a review
How can natural language processing help model informed drug development?: a review Open
Objective To summarize applications of natural language processing (NLP) in model informed drug development (MIDD) and identify potential areas of improvement. Materials and Methods Publications found on PubMed and Google Scholar, websites…
View article: Leveraging Real‐World Data for EMA Qualification of a Model‐Based Biomarker Tool to Optimize Type‐1 Diabetes Prevention Studies
Leveraging Real‐World Data for EMA Qualification of a Model‐Based Biomarker Tool to Optimize Type‐1 Diabetes Prevention Studies Open
The development of therapies to prevent or delay the onset of type 1 diabetes (T1D) remains challenging, and there is a lack of qualified biomarkers to identify individuals at risk of developing T1D or to quantify the time‐varying risk of …
View article: Application of machine learning to predict reduction in total PANSS score and enrich enrollment in schizophrenia clinical trials
Application of machine learning to predict reduction in total PANSS score and enrich enrollment in schizophrenia clinical trials Open
Clinical trial efficiency, defined as facilitating patient enrollment, and reducing the time to reach safety and efficacy decision points, is a critical driving factor for making improvements in therapeutic development. The present work ev…
View article: Remote Digital Monitoring for Medical Product Development
Remote Digital Monitoring for Medical Product Development Open
The use of digital health products has gained considerable interest as a new way to improve therapeutic research and development. Although these products are being adopted by various industries and stakeholders, their incorporation in clin…
View article: Open Data Revolution in Clinical Research: Opportunities and Challenges
Open Data Revolution in Clinical Research: Opportunities and Challenges Open
Efforts for sharing individual clinical data are gaining momentum due to a heightened recognition that integrated data sets can catalyze biomedical discoveries and drug development. Among the benefits are the fact that data sharing can hel…
View article: Machine Learning in Drug Discovery and Development Part 1: A Primer
Machine Learning in Drug Discovery and Development Part 1: A Primer Open
Artificial intelligence, in particular machine learning (ML), has emerged as a key promising pillar to overcome the high failure rate in drug development. Here, we present a primer on the ML algorithms most commonly used in drug discovery …
View article: Computational fluid dynamics analysis of a high-throughput viscous heater to process feces and a fecal simulant using temperature and shear rate-dependent viscosity model
Computational fluid dynamics analysis of a high-throughput viscous heater to process feces and a fecal simulant using temperature and shear rate-dependent viscosity model Open
Open defecation and poor fecal management facilitates the spread of disease. Viscous heating can pasteurize fecal sludge by creating a high shear field in the annular gap between a stationary, cylindrical outer shell and a rotating inner c…
View article: The feasibility of genome-scale biological network inference using Graphics Processing Units
The feasibility of genome-scale biological network inference using Graphics Processing Units Open
Systems research spanning fields from biology to finance involves the identification of models to represent the underpinnings of complex systems. Formal approaches for data-driven identification of network interactions include statistical …