A significant leap in biotech research and development has been achieved today with the announcement of Benchling Inference, a new platform that integrates Baseten's advanced AI capabilities to provide on-demand GPU resources tailored for scientific workloads. The need for efficient computation in drug discovery is at an all-time high, with the number of AI models used in scientific research soaring from 28 in 2020 to over 380 in 2025.
Addressing Infrastructure Bottlenecks
Biotech R&D workflows have faced challenges in managing computational resources. Drug discovery is often unpredictable, marked by bursts of activity that require rapid processing of large datasets. This has traditionally resulted in lengthy HPC queue times and underutilized GPU resources. Benchling Inference seeks to resolve these inefficiencies by providing a solution that allows biotech teams to avoid becoming experts in GPU management.
With Benchling Inference, companies gain access to a preloaded suite of leading scientific models, enabling immediate deployment and integration into existing workflows. The platform utilizes the Baseten Inference Stack, which combines high-performance runtime capabilities with extensive cloud provider support, ensuring cold starts can be achieved within 5 to 10 seconds.
Enhanced Flexibility and Economics
The platform is designed to meet the specific needs of biotech firms, including configurations for data residency that comply with regulatory standards. By pooling demand across the sector, Benchling aims to offer more competitive pricing for startups that might struggle with the costs of high-performance computing.
Benchling Inference allows scientists to deploy both third-party models and their own custom models derived from experimental data, all within a single compute environment. This flexibility is further enhanced by the ability to operate across various cloud configurations, including dedicated virtual private clouds.
Insights from Industry Leaders
Amir Highighat, CTO and Co-Founder of Baseten, stated, "Biotech has entered a new era where AI models trained on proprietary experimental data could enable breakthroughs that weren't possible before. The bottleneck has been infrastructure, and biotech research labs should not have to become GPU experts to run frontier models on their data. By partnering with Benchling, we bring six years of inference expertise directly into the environments where the science happens."
Ashu Singhal, co-founder and President of Benchling, highlighted the strategic advantage of access to compute resources. He remarked, "We've been running Baseten internally for Benchling's Model Hub and learned a lot about tailoring inference for drug discovery. Now we want customers to have the same access."
A Future-Ready Solution
As biotech R&D evolves, integrating AI capabilities like those offered by Benchling Inference is expected to speed up drug discovery. Efficiently managing and deploying AI models could lead to more timely insights and breakthroughs, ultimately benefiting patients and healthcare systems worldwide. Companies interested in leveraging this new infrastructure can sign up through Benchling’s platform, indicating a shift toward a more agile and responsive biotech sector.
Conclusion
The launch of Benchling Inference has the potential to transform how biotech firms approach R&D, offering a solution that alleviates the burden of infrastructure management while enhancing the potential for innovation in drug discovery. As the industry adapts to the rapid growth of AI applications, tools like these will be crucial for maintaining a competitive edge in a fast-evolving market.
