Overview
Generative AI (GenAI) is revolutionizing the life sciences and healthcare sector by accelerating drug discovery, supporting clinical trials, enabling precision medicine and streamlining healthcare operations.
The introduction of AI is ushering in more personalized healthcare solutions, optimizing resources and enhancing patient outcomes by analyzing large datasets to foster medical advancements.
HCLTech capitalizes on this transformation by harnessing our comprehensive AI ecosystem to offer a suite of platforms and life sciences-specific applications designed to maximize enterprise value.
Our end-to-end AI Lab provides extensive services ranging from GenAI-driven IT support and development to device engineering and industry-tailored solutions to upgrade service quality and enhance customer experience.
Explore the transformative impact of GenAI in life sciences and healthcare for personalized patient care and research advancements.
![Overview](https://hcltech.imgix.net/sites/default/files/images/business-pages/LSH_generative-ai-impact/overview-thumbnail.webp)
![GenAI in Life Sciences GenAI in Life Sciences](https://hcltech.imgix.net/sites/default/files/images/business-pages/LSH_generative-ai-impact/GenAI-in-Life-Sciences.webp)
GenAI in Life Sciences
The life sciences industry is increasingly adopting GenAI despite facing various challenges. Its appealing features — like no-code interfaces, predictive modeling and automation — drive its popularity. GenAI accelerates drug discovery, personalizes medicine and streamlines R&D, clinical trials, supply chain management and patient services, demonstrating significant value in the sector.
GenAI in Healthcare
The healthcare industry faces challenges related to customer interaction, operational efficiency, data management, regulatory compliance and fraud prevention. GenAl's distinctive capabilities, such as chatbots, synthetic data creation, process automation and content generation, have led to a paradigm shift in customer engagement, efficiency and cost-effectiveness.
![GenAI in Healthcare GenAI in Healthcare](https://hcltech.imgix.net/sites/default/files/images/business-pages/LSH_generative-ai-impact/GenAI-in-Healthcare.webp)
GenAI Industry Solutions and Platforms
Knowledge graph search
Our use case leverages large language models (LLMs) to process massive volumes of data across the enterprise to generate interconnected knowledge graphs, enabling more data-powered and holistic decisions. This removes the inefficiencies and delays from the existing process that requires niche and expensive skillsets.
Patient dropout and site prediction using historical data
This use case addresses the problem of clinical trial site-level patient dropout by providing proactive insights into patient phenotypes, clustering patients into risk levels and predicting their dropout probability.
Assisted case intake
Currently, the manual case intake process results in delays and errors. Our use case, built using LLMs and natural language processing (NLP) models, offers automated case extraction, interpretation, recommendation generation and potential adverse event identification to reduce the processing time, decrease errors and allow pharmacovigilance SMEs to focus on other key areas.
GxP document review/audit automation
The GxP document reviewer reduces the time and effort required to ensure documents are audit-ready and GxP-compliant by using GenAI-driven automated review of documentation practices across validation deliverables.
Guidelines comparison and insight generation
This solution addresses the highly manual and time-consuming operation of comparing large guideline documents by using automation and a GenAI tool trained on similar documents, resulting in a more efficient and improved process.
Patient-reported outcome measurement information system (PROMIS)
HCLTech’s PROMIS enables automatic patient information capture using a GenAI agent with text-to-speech and other capabilities to improve and personalize the patient hospital onboarding while eliminating the inefficiencies of the current manual process.
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