Insilico Medicine reported that it launched a preview version of its draft outline research assistant, Science42:DORA, to streamline the generation of scientific content.

According to Petrina Kamya, PhD, global head of AI platform, and vice president of Insilico, DORA integrates multiple AI agents that leverage LLMs, designed to streamline the process of drafting academic papers and other scientific documents including grant and patent applications, internal research summaries, IND applications, etc. It assists researchers in drafting these types of documents with proper referencing through engineered prompts, proprietary databases, and pre-designed content generation workflows, she added.

“Often the most difficult step when it comes to writing is starting the process. Something that I experienced first-hand as a graduate student when I was tasked with writing numerous grants, papers, and reports,” said Kamya. “We developed Science42:DORA to help eliminate that debilitating barrier to writing scientific documents.”

Insilico’s developers collaborated with researchers at the University of Copenhagen to submit a paper on medRxiv. The paper drafted by DORA and later manually curated and extended, performs a comparative study about radiotherapy outcomes across brain tumor types, namely glioblastoma multiform and low-grade gliomas based on radiotherapy phenotype and expression data from 32 cancer datasets.

Further tests planned

Insilico plans to further test DORA in multiple types of document generation and launch a free trial version of the AI assistant to the public in late 2024.

“We strive to integrate AI innovations with human intelligence for faster and better advancements in research and development, and LLM-based AI agents have been our recent focus,” noted Alex Zhavoronkov, PhD, founder and CEO of Insilico.
“With DORA, we hope not only to streamline the writing process but also to elevate the overall quality of scholarly output, which in turn powers practical applications and meaningful delivery.”

Insilico, which applies generative AI  to drug discovery and development work, described the concept of using generative AI for the design of novel molecules in Oncotarget in 2016. The company later developed and validated multiple approaches and features for its generative adversarial network (GAN)-based AI platform and integrated those algorithms into the commercially available Pharma.AI platform.

Since 2021, Insilico has nominated 18 preclinical candidates in a portfolio of over 30 therapeutic assets and has advanced seven molecules to the clinical stage, according to a company official. In March, the company published a paper in Nature Biotechnology that disclosed the raw experimental data and the preclinical and clinical evaluation of its lead drug—a potentially first-in-class TNIK inhibitor for the treatment of idiopathic pulmonary fibrosis discovered and designed using generative AI currently in Phase II trials with patients.

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