Predictive Analytics and AI: Unlocking Clinical Trial Insights
- 1. Welcome PREDICTIVE ANALYTICS AND AI : UNLOCKING CLINICAL TRIALS INSIGHTS Student’s : Shaik Nazeer Qualification : B pharmacy Student ID : CLS_038/042024 10/18/2022 www.clinosol.com | follow us on social media @clinosolresearch 1
- 2. Index • Introduction • The role of Predictive analytics • The role of AI in clinical trials • Benefits of predictive analytics and Ai in clinical trials • Case studies • Challenges and Considerations 10/18/2022 www.clinosol.com | follow us on social media @clinosolresearch 2
- 3. Index • Future Directions • Conclusion • Benefits and Challenges • Future Trends 10/18/2022 www.clinosol.com | follow us on social media @clinosolresearch 3
- 4. Introduction What is Clinical Trials ? • Essential for developing new treatments • Assess the Efficacy and safety of new drug, devices, and interventions Challenges in clinical trials • High costs • Long durations • High Failure rates 10/18/2022 www.clinosol.com | follow us on social media @clinosolresearch 4
- 5. The role of predictive Analytics Definition • Use of statistical techniques and machine learning to analyze historical data and predict future outcomes Applications in clinical trials • Patients recruitment • Prediction of clinical outcomes • Optimization of trial design 10/18/2022 www.clinosol.com | follow us on social media @clinosolresearch 5
- 6. The role of AI in clinical trials Definition • AI involves the simulation of human intelligence processes by machine • Applications in clinical trials • Natural language processing for data extraction • AI-driven data analysis for insights • Automation of routine tasks 10/18/2022 www.clinosol.com | follow us on social media @clinosolresearch 6
- 7. Benefits of predictive analytics and AI in clinical trials Enhanced patient Recruitments • Identify eligible patients more efficiently • Predict patient dropout risks • Optimized Trial Design • Use historical data to design more effective trials • Adaptive trials based on interim analysis 10/18/2022 www.clinosol.com | follow us on social media @clinosolresearch 7
- 8. Improved data quality and monitoring • Real-time data analysis to identify anomalies • Automated data cleaning • Data profiling and understanding • Data cleaning and standardization • Data governance • Quality assurance • Data monitoring and alerts 10/18/2022 www.clinosol.com | follow us on social media @clinosolresearch 8
- 9. Case Studies Case Study 1: Patient Recruitments • Example: AI models predicting patient eligibility • Result : Reduced time to recruit Participants Case Study 2: Predicting trial outcomes • Example: Predictive analytics in oncology trials • Result : Early identification of non effective treatment 10/18/2022 www.clinosol.com | follow us on social media @clinosolresearch 9
- 10. Changes and Consideration Data Quality and Integration • Ensuring high-quality, comprehensive datasets • Integrating data from multiple sources Ethical and Regulatory Issues • Ensuring patient privacy • Compliance with regulatory standards Interpretability Al Models • Ensuring Transparency in Al decision-making 10/18/2022 www.clinosol.com | follow us on social media @clinosolresearch 10
- 11. Future Directions Future Directions • Integration of Wearable Technology • Continuous data collection • Enhanced monitoring Personalization • Tailoring treatments based on predictive analytics Precision trials for targeted therapies • Collaborative AI systems • Combining human expertise with AI insights 10/18/2022 www.clinosol.com | follow us on social media @clinosolresearch 11
- 12. Conclusion Summary • Predictive analytics and AI hold significants potential of transform clinical trials • Potential to reduce costs,time and improve outcomes Call of action • Encourage stakeholder to invest in predictive analytics and AI • Foster collaboration between data scientists and clinical research 10/18/2022 www.clinosol.com | follow us on social media @clinosolresearch 12
- 13. Benefits and challenges • Increased Efficiency: Streamlined processes and faster decision- making • Enhanced Accuracy: More precise patient selection and outcome prediction • Cost Reduction: Lower costs due to optimized trial designs and reduced trial durations • Data privacy and security: Ensuring the confidentially and security of patient data 10/18/2022 www.clinosol.com | follow us on social media @clinosolresearch 13
- 14. Future Trends AI in Databases • Development of autonomous database that self-manage,self- tune,and self-heal • Example – Oracle autonomous database Emerging Technologies • AI-driven data for handling large volumes of diverse data 10/18/2022 www.clinosol.com | follow us on social media @clinosolresearch 14
- 15. Thank You! www.clinosol.com (India | Canada) 9121151622/623/624 info@clinosol.com 10/18/2022 www.clinosol.com | follow us on social media @clinosolresearch 15