Agilisium’s Data Lens Gen-AI Query Tool: Transforming Data Analysis in Pharmaceutical R&D and Healthcare

Pharmaceutical R&D and healthcare generate vast amounts of data from a wide range of sources, from preclinical and clinical trial results, through post-approval real-world drug use, claims data and medical records, to short- and long-term sales and marketing figures.

The challenges of drug development

Drug development is a costly and risky business. Median cost estimates per approved drug are as high as $2.8 billion, driven by failures at every stage of development, from discovery and preclinical research to late stage clinical trials. Drugs failing lose companies large amounts of money, damage their reputation (and their share price), and delay patient access to drugs that could change or save their lives. The impact of these failures increases at later stages, so a fail-fast strategy is vital.

To improve the chance of getting individual drugs to market, biotech and pharma companies need to be able to analyze as much of the available data as possible. The right data will help companies to:

Choose the right disease areas
Choose the right targets and drug classes
Choose the right patient populations
Assess the competition and the market landscape
Assess the possibility of a drug making it through clinical trials, and fail drugs early in development if necessary
Optimize clinical trials, including selecting the right patients, sites and investigators
Adapt clinical trials and select alternative approaches if required
Predict timelines
Create pricing strategies
Plan launches for the best time and the best locations
Create communications strategies
Create marketing and advertising strategies, and adapt as required
Optimize sales strategies, and evolve as needed
Plan post-approval studies
Extend drug lifecycles, with additional formulations and indications.

These decisions need to be made rapidly and backed up by solid evidence to meet the needs of the research teams and the shareholders, but the data analysis required can be complex and time-consuming. This needs the right tools.

The power of data query tools

Query tools allow users to interact with large datasets and extract and manipulate the data quickly and efficiently. Agilisium’s Data Lens is a query tool that combines generative AI and natural language processing, allowing users to query data in a conversational manner. The tool can analyze complex data sets and deliver information summaries tailored to the user’s needs.

Generative AI

Generative AI (Gen AI) models use neural networks to learn patterns and structure from training data in order to create new data. Gen AI can create a range of different outputs, including text, graphics, audio and video.

Gen AI’s applications in drug development and healthcare

Extracting information from data and documents.
Creating chemical and biological structures for drug development
Predicting synthesis routes for compounds
In silico screening
Indication selection
Predicting patient responses to drugs based on genetics
Identifying disease markers

How Data Lens supports the biopharma value chain

Agilisium’s Data Lens enables users to retrieve data quickly and efficiently and gain insights, providing data analysis support throughout the entire value chain, from first concept to the market:

R&D: Preclinical and clinical trials	Commercial: sales and marketing
Optimizing patient outcomes and supporting clinical trials Electronic medical record (EMR) analysis to extract insights	Creating pricing strategies Analysis of competitor sales and pricing data Analysis of payer data
Assessing drug cost-effectiveness and bridging current treatment options andunmet medical needs Claims data analysis to identify patterns	Making launch decisions, including timing and location Analysis of competitor launches
Optimizing drug development Clinical report data analysis to identify areas for improvement	Creating healthcare professional (HCP)-centric digital marketing Summaries of HCP-rep interactions to create personalized content
Optimizing site selection and trial efficiency Analysis of historical trial data, patient databases and real-time monitoring using feasibility assessments and risk mitigation	Enhancing product safety SClaims data analysis to identify patterns
Improving investigator selection and performance Profiling investigators and real-time monitoring of site performance using continuous feedback and risk mitigation	Optimizing sales strategies Sales data analysis to understand performance and identify opportunities
Monitoring treatment responses Identifying trends and variations across subjects, therapeutic modalities and study sites	Forecasting sales Sales data and market analysis to understand performance and identify opportunities
	Engaging better with HCPs Data on HCP interactions to improve engagement and comms

By helping decision-making, Agilisium’s Data Lens can help drug developers to get their drugs to market more quickly, efficiently and cost-effectively. This allows patients, especially those with rare diseases or with unmet medical needs, to get access to the drugs that they need to improve their outcomes or their quality of life.
To find out more about how Agilisium’s Data Lens can help you to get the most from your data, contact sales@agilisium.com or visit www.agilisium.com.

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