Data Science and Analytics

Key Features

Elimination of inefficiencies, wastages and leakages
  • The Data Science and Analytics solutions enable organizations, sponsors and other stakeholders in clinical systems to reduce drudgery and repetitive tasks, eliminate redundancies (data-related and process-related), minimize costs, wastages and leakages.
  • Enables you to drive efficiency in the clinical trial processes and ensure faster time-to-market and enhanced revenue flow.
Accurate, cutting-edge predictive models
  • We build accurate, cutting-edge predictive models to help you predict future outcomes of your clinical trial processes with ease and offer actionable insights to empower you to make informed, real-time decisions.
Customized solutions built by elite team of experts
  • Fresh Gravity’s team consists of experts in data science and analytics, business strategists, computer scientists, life science experts, business process architects and others. Our team of elite experts custom-build every solution with surgical accuracy to meet your organization’s unique needs.
Key partnerships with leading technology vendors
  • Our deep expertise in the life sciences industry combined with partnerships with leading technology vendors enables us to offer next-gen solutions for enhanced outcomes in a multitude of life science use cases.

Use Cases & Capabilities

 

Clinical Trial
Design
 

Leverage data analytics, ML/AI and deep learning techniques to analyze clinical and operational data and response to drugs, predictive modeling to determine site and study performance, patient response to drugs and patient continuation in clinical trials.


Signal Detection
in Pharmacovigilance
 

Accurately identify “signals” that suggest a new potentially causal association or a new aspect of a known association between an intervention and related events.
 
 

 

Improving Patient
Conversions
 

Use insights from advanced analytics to take decisions on enhancing patient engagement, craft frictionless experiences and drive better patient retention.


Chargeback Anomaly
Detection
 

Prevent revenue leakage from sales transactions by using AI/ML solutions to effectively analyze operational and sales data arising from chargeback processes.
 


Clinical Trial
Design
 

Leverage data analytics, AI-ML and deep learning techniques to effectively analyze clinical and operational data, responses to drugs, etc. Leverage predictive modeling to determine site and study performance, patient response to drugs, patient continuation in the clinical trial and whether the trial will be successful. Use the insights to design your clinical trials appropriately.


Risk-Based
Monitoring
 

Consistently and effectively monitor the performance and quality parameters of multiple vendors (CROs), diverse clinical trial sites, the study and portfolio. Identify critical data and processes to remotely/centrally monitor risks and proactively identify and mitigate inefficient site behavior and processes. Effectively monitor patient and study safety, ensure early detection of issues and save resources. Ensure better compliance.


Signal Detection in
Pharmacovigilance
 

Effectively analyze information that arises from one or multiple sources using Fresh Gravity’s data science and analytics solutions. Accurately identify signals – patterns that suggests a new potentially causal association or a new aspect of a known association between an intervention and related events, either adverse or beneficial – that are judged to be of sufficient likelihood to justify further verification.


Improving Patient
Conversions
 

Leverage AI, ML and deep learning techniques to gain actionable insights on patient experiences with the treatment/ drug/ therapy and outcomes. Use these insights to take effective decisions to further enhance patient engagement, craft frictionless experiences and drive better patient retention. Improve your clinical research outcomes and business value.


Chargeback Anomaly
Detection
 

Leverage our AI-ML solutions to effectively analyze operational and sales data arising from the chargeback processes to ensure timely and prompt detection of any gaps, loopholes and opportunities for bad transactions or frauds. Accordingly, prevent chances of revenue leakages from such transactions.