Our customer, a global pharmaceutical leader, faced significant hurdles in their R&D process. The sheer volume of documents, including research papers, patents, and internal reports, overwhelmed the team. Manually analyzing and extracting crucial information from these documents was time-consuming, error-prone, and hindered the overall R&D efficiency.
Large Language Models (LLMs)
Machine learning algorithms
Document processing libraries
Cloud-based solutions
Intuitive User Experience (UX) Development/ Design
Research and development in pharmaceuticals – particularly documentation and reporting, has been conventionally manual and time-intensive. On the one hand, there is a constant influx of data spanning record-keeping, research and development insights, inventory, product lifecycles, and compliance documentation. Conversely, there is an increased focus on cutting costs by improving efficiency, shortening R&D timelines, and elevating quality management. Balancing surging innovation and cost optimization requires automating time and process-intensive tasks, gaining real-time visibility into operations, and identifying hidden patterns to improve decision-making.
A leading pharmaceutical company faced similar hurdles in its R&D process due to extensive data volume, including research papers, patents, and internal reports. The entire cycle was not just time-consuming but also took up a considerable part of human efforts, which could otherwise be channeled into other constructive tasks. Moreover, manual vetting of documents to extract relevant information also led to errors and inaccuracies. Such inefficiencies led to prolonged delays and hindered the overall efficiency of the R&D pipeline. They sought an advanced solution to streamline and elevate the quality of their information retrieval and output.
Such inefficiencies led to prolonged delays, which increased time-to-market, hindering the overall efficiency and impacting cost and revenues.
They sought an advanced solution to automate and streamline information retrieval and output, elevate the quality of the R&D pipeline, and maximize cost-effectiveness.
Bosch SDS identified the need for a GenAI-based solution that could reduce errors during documentation analysis, save time and elevate the R&D pipeline. We implemented a GenAI-based document analyzer solution. This advanced platform incorporated features such as smart summarization, real-time document training, and document comparison. Key capabilities of the solution were:
Bosch SDS’ GenAI-based document analyzer transformed the way the pharmaceutical company handled information – enabling enhanced R&D efficiency and accelerating turnaround time for document analysis, comparison, and insight extraction.
Upto 90% reduction in search time
Accelerated R&D process
Reduced manual errors
Improved efficiency
Our GenAI-based document analyzer helped our client overcome technical and workflow challenges by seamlessly integrating with their organizational systems. Through our advanced algorithms complemented by LLM models, the client was able to analyze vast amounts of data across their research projects to create innovative drug models, predict outcomes of combinations, and forecast potential adverse effects of new vaccines. With real-time learning capabilities and a user-friendly interface, our platform empowered researchers to focus more on innovation rather than resolving data silos and discrepancies – accelerating vaccine and drug development.
