Prescriptive Insights: Provide recommendations based on the predictions, such as adjusting the treatment plan for a patient at high risk of dropping out.
Patient Clustering: Group patients based on their similar characteristics or phenotypes.
Learning from Past Data: Learn from their historical trial data and gain insights into patient populations at higher risk.
AE Profiles: Captures patient history of
adverse events.
Likelihood Prediction: The AE profiles are used to predict the likelihood of a patient’s future dropout based on the identified susceptible phenotypes.
Train a classifier for drop out on historic
data that can predict well on ongoing
studies
● Python
● Tableau
● AI/ML Model (Auto ML)
● Generative AI (Gemini)
Enhanced Patient Experience: Personalized care and reduced burden on patients.
Visuals on weekly drop-out
prediction, post each visit data collection with patient level details
Alert for patients in high-risk clusters and with high likelihood of drop out
Reduced Costs: Minimize
trial failures and associated
expenses.
Improve the efficiency and engagement of their offline pre-medical questionnaire
process.
Patients find it difficult to complete lengthy questionnaires.
Lack of standardization in PROMIS 29 data collection hinders comparative analysis and research.
Efficiency: Automated data collection reduces administrative burden and
improves efficiency.
Accuracy: AI-powered conversational agents ask personalized questions for
consistent and accurate data capture.
Patient Experience: A conversational interface provides a more engaging and user-friendly experience for patients.
● Python
● Gemini Pro 1.5
● BigQuery
Improved Decision Making:
Accurate and standardized data
collection.
Reduced Costs: Automation help to reduce operational costs associated with data collection.
Increased Patient Satisfaction: A more efficient and engaging patient experience
Human-generated summaries are time-consuming and inconsistent.
Scalable and efficient solution to summarize large volumes of text.
The quality of summaries vary depending on the expertise and experience of the human summarizer.
Efficiency: Gen AI can generate
summaries quickly and efficiently.
Consistency: Maintain a consistent style and tone for AI generated summaries,
Handle large volumes of text without compromising quality.
● AI Act
● GAMP 5 Compliance Guideline comparison
● AI Act comparison with SOPs
● GPT-3, Azure Cosmos DB, Elastic Search