VIRTUALMAN Breaking Barriers in Drug Development with AI Solutions

by Kathy Huang
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VIRTUALMAN has released two AI platforms to empower drug development, VIRTUALMAN for ADMET/PK and ADDD Platform. VIRTUALMAN for ADMET/PK is built to accurately predict the properties of molecules, powered by the GCN (Graph Convolutional Networks). ADDD Platform is designed to optimize compounds while considering simultaneously the efficacy and safety. The capability comes from the combination of GCN and Reinforcement Learning.

In BIO Asia-Taiwan 2021, VIRTUALMAN showcased its AI technologies in a webinar, discussing current difficulties in AI drug development and demonstrating how AI technology will revolutionize traditional drug developments and significantly benefit pharma companies.

Full webinar of VIRTUALMAN’s Presentation on AI Drug Development:

VIRTUALMAN, headquartered in Taiwan, focuses on virtual high-throughput screening and lead optimization to accelerate drug development. Furthermore, their services moderate the issue of digital transformation for small and medium-sized pharmaceutical companies.

“There is a huge need for pharma companies to quickly identify novel compounds and push compounds through the discovery and development obstacles. Also, going through the traditional in vitro and in vivo route for identifying drug efficacy costs lots of time,” Professor Yufeng Jane Tseng, co-founder of VIRTUALMAN pointed out.

Specifically, the traditional process of drug discovery and development takes ten to fifteen years and costs more than US$300 million on average. Besides, it is hard to find proper targets in the drug discovery stage, so improving the ability to conduct efficient prediction is the latest trend in AI drug development

“In traditional drug development, safety and Pharmacokinetics properties are usually considered in the later stages, but if the properties are not favorable, it is challenging to optimize them and maintain efficacy at the same time,” Yun-Cheng Tien, CEO of VIRTUALMAN pointed out.

The first solution to this obstacle is to take safety and Pharmacokinetics properties into account early in the development process. VIRTUALMAN for ADMET/PK is powered by the GCN, the latest powerful algorithm that allows accurate prediction with limited data. Moreover, VIRTUALMAN for ADMET/PK was equipped with Explainable AI technology to explain data results and evaluation processes to the researchers.

Liu Hsin, CTO of VIRTUALMAN, mentioned that this new technology breaks the black box for pharma companies to eliminate the concerns of adopting AI solutions.

VIRTUALMAN for ADMET/PK provides various endpoints, including binding prediction, physical properties, Metabolism, Toxicity, Pharmacokinetics, Absorption, etc.. VIRTUALMAN also support clients to develop the model based on their private data with the customized AI services.

The second solution is to optimize multiple properties simultaneously. VIRTUALMAN ADDD Platform sheds light on this solution. Once pharma companies provide multiple expected properties and compound structures, the platform will automatically optimize and synthesize them and generate more than 1,000 compounds that meet all the parameters within three weeks.

After that, the compounds will undergo drug metabolism/pharmacokinetics (DMPK), ADMET (absorption, distribution, metabolism, excretion, and toxicity), and off-target evaluation, and the researchers will obtain compounds with a higher success rate in preclinical trials.


The high compatibility of AI-driven solutions reduce the cost of R&D

VIRTUALMAN has plenty of successful cases on introducing the AI platform in drug development. For example, pharmaceutical companies use VIRTUALMAN for ADMET/PK to screen compounds before purchasing them, narrowing tens of thousands of options to dozens of preferable options. With the benefit of AI platforms, researchers can easily advance the R&D process to the next stage.

Through the ADDD platform, researchers can quickly identify compound performance and taking drug efficacy and toxicity into account simultaneously. Professional researchers might take several months on average to conduct the process in the traditional method, whereas AI platforms can shorten the period to less than 1 month.

Yun-Cheng Tien, CEO of VIRTUALMAN pointed out that the high compatibility of AI solutions can reduce the cost of IT investment. Small and medium-sized enterprises won’t need to build AI systems from scratch, purchase hardware equipment, or spend extra maintenance costs. By introducing AI solutions, pharma companies can greatly improve their competitiveness and solve insufficient staffing.


Catching up the AI Drug Development Trends

The trends in digital transformation are unquestionable in many industries, and many global pharma giants have introduced AI technology to enhance the efficiency of drug development. But in Taiwan’s case, Taiwanese enterprises are primarily small and medium-sized, lacking sufficient resources for investing in AI technology. Besides, building an effective in-house IT team remains a significant obstacle in digital transformation for the pharma companies.

AI-driven drug development will shape the future of pharmaceutical industry. Dr. Chun-Yi Lee said that the implementation of AI solutions in the pharmaceutical industry has gradually risen in recent years, and so many well-known big pharmas have stepped into AI investment. AI can make up for pharma companies’ shortage of production capacity and help them effectively implement R&D strategies in international and local markets.

VIRTUALMAN will strengthen the business in Europe and North America markets on their cooperation with Silicon Valley and Boston bioclusters. They have obtained million-dollar funding from Acorn Campus Taiwan, the Silicon and Taiwanese venture capital, in 2020. VIRTUALMAN will deepen the AI solutions and accelerate the AI-driven drug development for the pharmaceutical industry.

Free trials for VIRTUALMAN’s AI solutions:
ADDD demo:
SaaS demo:

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