Create a visually appealing and easily scannable case study. The design should incorporate relevant images, tables, and boxes to enhance readability and allow for quick information retrieval. Maintain the original text content without any modifications. The layout should prioritize visual clarity and efficient information presentation, ensuring that key findings and data are immediately accessible to the reader. The design should be modern and professional, suitable for online publication and easy consumption.

Banner Shortened Systematic Review Process by 99% using AI Summary Before: 1 year | After: 50 hours Conducting a Systematic review is the first step in drug development. It can take up to a year. We developed an AI-powered tool that relieves researchers from time pressure. The systematic review process takes less than 50 hours, a significant reduction. Here’s how we did it. About the client Medical Researchers from the UK Our clients are UK-based medical researchers with 15+ years in the industry. They perform systematic reviews, a key step in pharmaceutical companies' drug development processes. They have first-hand experience of reading up to 100 studies as a part of this review. They sought to empower themselves and their fellow medical researchers with a time-saving tool.

Requirement Streamline Medical Research Developing a drug takes 10 to 12 years. Billions of dollars are invested in it, and research is its bedrock. What they had? The client came to HestaBit with a scrappy research tool and wanted to turn it into an impactful product. What they wanted! AI-based tool to save time spent in the review. The nitty-gritty The biggest part of this process is finding relevant data. There are thousands of studies on almost every keyword. The goal is to find problems, gap areas, diseases, specific cures for diseases with existing medications, lower prices, improve efficiency, etc. This involves reading through each study, understanding its findings, and then synthesizing the information into a comprehensive review. It's a time-consuming and labor-intensive process. Problem Statements Where do medical researchers go for information? The majority of researchers use PubMed, a free and universally accessible database run by the National Library of Medicine (NLM) under the National Center for Biotechnology Information (NCBI) in the USA. Finding relevant papers One keyword has 100+ research papers. Finding relevant papers is a very time-consuming process.

Beta testers were lined up. The client spread the word in their community, and people were eager to get their hands on the final version. Instead of 12-18 months, the systematic review could take only 48 hours.

Tech Solution Finding relevant studies in the database of 36 million

Result AI-powered innovation meets today’s needs The differentiator! Traditional PubMed Search The New Tool The PICO framework is commonly used for quantitative systematic reviews. It involves the patient/population, intervention, comparison, and outcomes. While conducting research in traditional Pubmed searches, users must search separately for insights into specific parameters.

We incorporated an inbuilt feature for niche searches into an LLM trained on medical terms. The tool can generate answers based on the PICO format. Using an AI algorithm, it understands the intent behind the query, so the researcher can get more information than PubMed can provide. This AI tool works by analyzing the query, identifying the key parameters, and then searching the database for relevant studies, all in a matter of seconds. We made this happen by using medical LLMS.

Next step: This project began by focusing on streamlining systematic reviews. After accomplishing that, we shifted our efforts to shortening the entire drug development process. This AI-powered innovation not only meets today’s needs but also paves the way for future advancements in medical research.