inThought Research Inc., a specialist in decision support for the life sciences industry, has unveiled a new artificial intelligence (AI) strategy aimed at improving efficiency in drug discovery. The company’s plan includes the use of machine learning and large language models (LLMs) to streamline time-consuming tasks while ensuring compliance and security. By collaborating with pharmaceutical firms, inThought aims to transform everyday processes from information gathering to insightful decision-making.
As industries face the challenge of processing vast quantities of data and conflicting information, decision-makers often struggle to identify the most relevant insights. inThought Labs, the company’s technology division, is working closely with drug makers to develop solutions that leverage both human and artificial intelligence to meet these challenges.
inThought’s AI solutions are designed to reduce the burden of information overload by automating tedious tasks such as sorting data and summarising documents. This approach allows researchers and analysts to focus more on generating insights and making informed decisions.
One of the key innovations announced is a machine learning-based system for screening updates on clinical trials. This solution monitors the clinicaltrials.gov database for changes relevant to specific drug indications or compound names. The system ranks these updates based on importance, learning from user feedback to improve accuracy over time. Users can quickly identify critical trials while ignoring irrelevant updates.
“While there may be hundreds of changes relevant to your keywords in the clinicaltrials.gov database each week, our system quickly learns what is important to you,” a spokesperson for inThought explained. “It highlights trials that are definitely important, ranks others as possibly relevant, and suggests which updates can be ignored. The ranking improves each time as the system learns from your feedback.”
The company has also introduced AI-driven tools to assist with summarising scientific and medical conference materials. Using generative AI, the system can quickly produce summaries of abstracts, helping teams to efficiently scan through posters and oral presentations. A future update will provide enhanced summarisation of conference slides and graphs.
Another notable feature is the integration of generative AI into inThought’s proprietary inVision platform, which enables users to securely summarise a wide range of content, including press releases, earnings reports, and conference notes.
inThought’s AI strategy places a strong emphasis on maintaining confidentiality and regulatory compliance, key concerns for the pharmaceutical and biotech sectors. The company’s inVision platform is SOC2 compliant, ensuring that data is handled securely and in accordance with industry standards.
The company has invited its partners in the drug discovery industry to collaborate on further AI developments. “Our AI experts understand the regulations and confidentiality concerns of both the pharmaceutical/biotech industries and the AI development landscape,” the spokesperson added. “We are committed to helping our partners develop AI-based solutions that reduce the tedious and allow for a greater focus on innovation and insight.”
For more information about inThought’s AI-driven solutions, visit their dedicated pages at www.inthought.com/ai and www.inthoughtlabs.com/ai.
