![Atlanta-based-InpharmD-Secures-6.05M-in-Funding Atlanta-based InpharmD Secures $6.05M in Funding. 645 Ventures led the funding round. Atlanta Ventures, Y Combinator, Qlarant Capital, SF ELC, and angel investors were amongst the other investors. The vice president of 645 Ventures, Jon Smith, will be joining the board of directors of InpharmD.](https://startuprise.io/wp-content/uploads/2023/12/Atlanta-based-InpharmD-Secures-6.05M-in-Funding.webp)
![Atlanta-based InpharmD Secures $6.05M in Funding. 645 Ventures led the funding round. Atlanta Ventures, Y Combinator, Qlarant Capital, SF ELC, and angel investors were amongst the other investors. The vice president of 645 Ventures, Jon Smith, will be joining the board of directors of InpharmD.](https://startuprise.io/wp-content/uploads/2023/12/Atlanta-based-InpharmD-Secures-6.05M-in-Funding.webp)
Atlanta-based InpharmD Secures $6.05M in Funding. 645 Ventures led the funding round. Atlanta Ventures, Y Combinator, Qlarant Capital, SF ELC, and angel investors were amongst the other investors. The vice president of 645 Ventures, Jon Smith, will be joining the board of directors of InpharmD.
The money will be used by the company to expand both its operations and its clientele. InpharmD, which was co-founded by Ashish Advani, PharmD, and Tulasee Rao Chintha, PharmD, allows evidence-based care by providing on-demand drug information and leveraging the knowledge of pharmacists to create customised, data-driven answers to clinical requests and formulary requests.
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Furthermore, it facilitates economical decision-making by recommending data-driven treatment exchanges and procedures that reduce hospital stays for patients. The startup saves two hours and summarises 12 clinical studies per search for over 100 hospitals and 10,000 doctors by partnering with 11 health systems and integrating with methods like Epic and Alexa.
InpharmD has been collecting a library of 30 million clinical research over the course of two years. To search and summarise pertinent material, it combines massive language models—both proprietary and open source—into its system. Clinical chemists use reinforcement learning to make sure the search and summaries are ideal for the final clinician user and to enhance the algorithm for the subsequent search.
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About InpharmD
In order to help healthcare professionals make better decisions, InpharmD want to offer them with improved access to health information. Through their website and mobile application, they link queries from healthcare providers to tailored, empirically supported answers from a national network of academic drug information centers—all optimised with machine learning.
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