Industry Context and Challenges
Clinical Trial Failure & Delays: ~85% of clinical trials face delays, primarily due to slow patient recruitment, which massively inflates costs and delays revenue generation.
Data Fragmentation & Quality: Scientific, clinical, and commercial data are locked in siloes across legacy systems, preventing the holistic, real-time insights required for AI model training.
AI Led Digital Transformation Challenges: Numerous pilots, lack of overarching digital strategy and implementations, lack of an aligned Strategic Workforce Planning (SWP) and change management / governance lead to only partial realization of benefits
LS-SACS Approach and Services​
LS-SACS has introduced a comprehensive set of methodologies to ensure small, medium and large life sciences organizations realize the true benefits of Ai-led digital transformation in a timely manner.
Holistic Ai-led Digital Clinical Transformation Framework - AiDCT
HAiDCT is a comprehensive and rapid approach that guides the organization from a "best-in-class" strategy through a maturity assessment, business case development and finally a phased implementation roadmap.
Ai-led Digital Clinical Maturity Assessment (DCMA)
DCMA evaluates a company's AI driven digital clinical maturity across 10 core parameters that include strategy, phased implementation, operating model, strategic workforce planning (SWP) and risk / compliance. This allows companies to see their own current status (staff and external benchmarking), identify gaps and develop a customized and phased implementation plan for tangible benefits.
Estimated cost savings by trial process due to AI
Optimal order of digital clinical initiatives roll out
Expected Benefits
Holistic Ai-led digital clinical transformation approach can allow clinical operations to develop the optimal business case as well as an effective roll out / phased implementation plan