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Mar 24

Partex NV announces collaboration with Althea DRF Lifesciences to provide comprehensive end-to-end services to accelerate drug discovery and development

Frankfurt, Germany; 28 March 2024 – Partex Group, a pioneer in AI-driven drug discovery, announces a collaboration with Althea DRF...
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18

Mar 24

Innovative AI technology in oncology: Partex Group presents results from a pilot project

During the German Cancer Congress 2024 in Berlin, the companies Innoplexus AG /Amrit AG, companies of Partex N.V., presented the...
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Innoplexus wins Horizon Interactive Gold Award for Curia App

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New Blockchain Platform from Innoplexus Will Bring Us Better, Cheaper Drugs

Redundancies in any professional field mean dollars lost. But in healthcare, inefficiency can cost lives.

That’s a reality that Gunjan Bhardwaj came to understand when his friend and mentor was diagnosed with cancer. When Bhardwaj accompanied him during grueling rounds of chemo, he was appalled at the lack of information evidence from which to draw a personalized, targeted treatment plan. Though his friend survived, the experience alerted Bhardwaj to the information gaps created by publishing bias in the healthcare industry, and set out to fill those gaps through his company, Innoplexus.

Failed Experiments and the Publishing Bias

Founded in 2011, Innoplexus has since become the premier AI and Big Data innovator for pharmaceutical companies. Innoplexus has offices in Germany, India, the United States, and over 20 clients globally, many of whom constitute Big Pharma. The company’s reliance upon AI and machine learning sets them apart, and they are pushing the envelope even further by debuting a new blockchain-based platform to solve one of the biggest problems in drug development: the loss of data from failed experiments.

When Bhardwaj’s friend fell ill, he took note of the lack of information on what studies have been conducted but did not work. Now, using machine learning, AI, and the blockchain, Innoplexus is seeking to remedy that dearth of information. Bhardwaj sees the benefits of the blockchain in particular as a logical tool in pharma.

“Blockchain is a natural fit for pharma, where data security and data transparency are equally important for innovation,” he said.

Generally, publishing bias is to blame for the lack of information about failed experiments. Researchers typically don’t seek attention for their failed studies, as they are seen by some as wasteful endeavors. And those who publish scientific journals aren’t generally interested in the studies that didn’t yield significant findings. For these reasons, data pertaining to “unsuccessful” clinical trials often go by the wayside.

This is a major problem that leads to massive redundancies in the market. Countless hours and dollars are wasted by researchers who, because there is not a reliable database of research documenting failed experiments, conduct similar or identical experiments that have predictably disappointing results. Allocating time and money to experiments that have already been conducted has almost certainly cost lives.

A Blockchain-Based Solution

Minimizing these inefficiencies in clinical research by making both successful and unsuccessful findings available on a blockchain-based platform is precisely the need that iPlexus aims to serve.

“So many useful insights get lost when data from failed experiments goes unreported. By giving researchers a secure platform to share these insights, we will cut back on duplicative work and accelerate the pace of innovation,” Bhardwaj said.

The platform will be a secure forum on which researchers can upload and license their findings pertaining to preclinical life science research and drug discovery. Information about failed experiments will be searchable right alongside the data from successful ones, and original findings will be given greater weight, plus a higher price, than those considered duplicative. Researchers’ intellectual property will be protected through the issuance of an immutable timestamp, ensuring that plagiarism and fraudulent attribution are not of concern.

AI and machine learning will serve to evaluate the data for originality, and will refer relevant data pertaining to ongoing trials. The ability to upload findings in real time is a means to bypass the time-consuming process of peer review, which can chew up months of time, is subject to publishing bias, and can contribute to the inefficiencies in the system.

Ultimately, this streamlining of how clinical research is shared and accessed will benefit those conducting the experiments, but it will benefit the patients as well. Faster, more targeted research and development processes and higher success rates in clinical trials are two of the clearest outcomes of the iPlexus database. With a broader knowledge of what studies not to conduct, researchers will no longer be flying blind into their experiments, allowing them to formulate and design their experimental processes more intelligently. In the end, the lower cost created by reducing redundant R&D will be passed along to the patient.

“More sharing of insights and data means more creative research, more successful clinical trials, and faster innovation. The end result is more effective, less expensive drugs for consumers,” Bhardwaj stated.

The original article was published on Coinstaker.

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