Improving targeting precision and field force direction through AIML-based patient finding

Home / Intelligence / Case Studies / Improving targeting precision and field force direction through AIML-based patient finding

Background

A global rare disease company was looking to improve targeting precision and support field team effectiveness
Traditional targeting was non-viable due to the small size of the patient populations, complex disease recognition and diagnosis, and restrictive therapy eligibility criteria

Attempts by a prior analytics partner to use rule-based alerts failed, and even after two years, no new patients had been identified

Given the small number of patients in each indication, every new start is high value, both for the lives of patients in need and for the commercial success of the therapies

Trinity’s Solution

Create an AIML model that identifies clinically on-label patients—rather than simply patients with the disease
‘Learn’ from on-therapy patients to identify how patients present prior to therapy initiation and execute AIML models to flag patients based on the probability that they are candidates for treatment
Deploy bifurcated notifications to both inside and field-based reps through ‘push’ alerts within the client’s CRM and enable ‘pull’ solutions to support call planning
Success drivers include:
- Data acumen to evaluate and select source data
- Therapeutic area expertise
- Deep collaboration with Medical to refine and calibrate models
- AIML experience to optimize feature selection and approach

Project Outcomes

Designed and deployed AIML models for three indications in 8 weeks

Narrowed field team focus from >25,000 HCPs to ~1,000 highest priority HCPs

Identified 100 high probability targets within first 2 months of launch

Patients confirmed through Machine learning.

At least 5 patients confirmed to be clinically on-label for therapy within first 2 months

First new patient enrolled within 5 weeks of initiating alerts

If you have any questions, we’re here to answer them.
We look forward to helping identify solutions for you.

Ask Us A Question

Related Intelligence

Webinars

Unlock the Potential of Generative AI in Life Sciences Insights and Operations

May 2, 2024 | 1:00 – 1:45 PM ET

Two additional sessions will be offered: May 3, 2024 | 15:00-15:45 CET – Europe/Berlin May 8, 2024 | 16:00-16:45 (UTC+8:00) – Asia/Shanghai Generative AI (GenAI) has created an opportunity to re-think and significantly improve how we work. Although far from replacing humans, GenAI has the potential to make pharma professionals far more effective and valuable […]

Case Studies

Early Adopter Identification Engine

In order to plan and efficiently utilize their sales and marketing efforts, a mid-sized biopharma client wanted to identify HCPs likely to adopt their drug in the early stage of launch

Case Studies

Dynamic Targeting Solution

A large biopharma customer wanted to develop a dynamic targeting solution for HCPs in a particular market