Machine learning to streamline study initiation and setup.pptx

Machine learning (ML) offers a transformative solution to these challenges. By leveraging advanced algorithms and data-driven insights, ML can streamline and optimize the study initiation and setup process. This technology enables automation of routine tasks, enhances decision-making through predictive analytics, and ensures data consistency and compliance with regulatory standards.

1. Machine learning to streamline study initiation and setup Dr Nidhina BDS ID:078/062024 MAIL:[email protected]

2. G lossa ry INTRODUCTION STEPS INVOLVED IN SI AND SS ROLE OF MACHINE LEARNING IN INITIATION ROLE OF MACHINE LEARNING IN SET UP ADVANTAGE IN CT

3. Machine learning Development of algorithms and models that enable computers to learn from and make predictions or decisions based on data Study initiation phase where all necessary preparations are made to start a clinical study smooth and ethical conduct of the trial Study setup involves meticulous planning, coordination, and preparation of all aspects necessary to initiate and conduct a clinical trial successfully

4. STEPS INVOLVED in study Initiation And Set up Literature Review Study Design Participant Recruitment Protocol Optimization Risk Assessment and Management STUDY INITIATION STUDY SET UP Protocol Developmen t Regulatory and Ethical Approvals Site Selection and Preparation Investigator Selection and Training Participant Recruitment and Informed Consent Data Management and Monitoring Safety Monitoring and Reporting

5. Machine leraning LITERATURE REVIEW COMPREHENSIVE INSIGHT Patient data Suitable trial patients Better outcome CONSTANT DATA ANALYSIS/RTM Detect trends/anomalies Study integrity ANALYSE ETHICAL ASPECT ADHERE ETHICAL STANDARD

6. In summary, machine learning offers numerous advantages in study initiation by automating tasks, improving decision-making through data analysis, and enhancing overall efficiency and effectiveness in the research process. Integrating ML into study initiation processes has the potential to accelerate scientific discovery and improve outcomes in various research domains.

7. MACHINE LEARNING IN TRIAL SET UP Machine learning in clinical study setups refers to the application of ML techniques to various aspects of designing, conducting, and analyzing clinical studies

8. Machine learning electronic health records Eligible participants Time /resource management ANALYSE RISK PROFILE TARGETED INTERVENTION STUDY OUTCOME Data Quality Control MONITOR DATA QUALITY RELIABLE DATA MINIMIZED DATA CLEANING POST STUDY Adaptive Trial Design modify trial protocols optimize study parameters

9. MACHINE LEARNING Biomarker Identification predict treatment response personalized medicine approaches Image Analysis analyze medical images extract quantitative features image-based diagnostics Drug Repurposing biomedical data predict adverse drug reaction enhanceD pharmacovigilance Ethics and Bias Detection mitigate biases transparency VALID RESULTS

10. Overall, integrating machine learning into clinical study setups enhances efficiency, accuracy, and the ability to extract meaningful insights from complex datasets. This not only improves the quality of clinical research but also facilitates the development of innovative treatments and personalized healthcare solutions.

11. THANK YOU