THE FUTURE OF DRUG DISCOVERY IS HERE
AI Techlife platform
Our patent-pending AIBioPharma Solution
We’re Changing the Way the World Thinks About Drug Discovery
The primary goal of AI Techlife is to bring down the cost of medicine for pharmacologists, biologists, physicians, pathologists, and scientists who require it.
AI Techlife will achieve this through the AIBioPharma Solution, which will make the drug development process faster, more efficient, and more cost effective for labs, clinics, pharmaceutical companies, and hospitals that are involved in the creation of new medications in the market.
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AI Techlife hopes to revolutionize not only the way pharmaceutical companies collaborate on clinical trials, but also the way they set up, conduct, and oversee the operational and clinical effectiveness of their trials by developing AIBioPharma Solution, which focuses on specific key pain points and bottlenecks for effect predictions in the drug development process.
The AIBioPharma Solution is a biological effect and safety prediction system and a platform for using data analytics and machine learning to reduce drug development costs.
The AIBioPharma Solution platform from AI Techlife Inc. focuses on a critical pain point in drug development making effect and safety predictions faster by adding machine learning and data science into the drug development process.
A fully automated system without human interaction
AIBioPharma Solution uses historical health data to predict drug effects, future and proactively address issues before they arise.
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AI Techlife's aim is to reduce costs by offering competitive clinical drug effect and safety prediction services. Pharmaceutical companies will now acquire a deep understanding of the operational and clinical aspects of their trials without having to invest heavily in backend technical infrastructure or data science expertise.
The AI Techlife sets itself apart from existing drug development tools by:
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Allowing the prediction of drug effects on cells earlier in the process, which "closes the loop
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Removing the requirement for client-borne hardware expenditures
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Using powerful data analytics functionality across operational and clinical tasks in clinical trials
Drug effect predictions can be performed using current clinical data and historical clinical data to
better inform trials moving forward.
The massive volume of data acquired during a clinical trial opens up a lot of opportunities for predicting drug effects that influence a clinical trial's potential to discover successful medications and detect drug side effects in the human body. Regulators, on the other hand, can accept these forecasts as evidence of the drug's efficacy and safety. The AIBioPharma Solution platform will integrate all clinical data sources and employ machine learning models to forecast drug effects, issues, and events.
AI Powered Cancer
Drug Discovery
AIBioPharma Solution analyzes health data to identify early warning signs that the applied medicine does not provide safe results and a different medicine might be required to get applied. Our approach has not been fully utilized to date since predictive modeling is not yet widely used to forecast cell phenotypes. The AIBioPharma Solution application will discover hidden connections across all datasets using our generated data and customer data, allowing the pharmaceutical company to take proactive actions.
For example, predicting in week No. 2 that a medicine will deliver a specific effect in week No. 12 would allow a pharmaceutical company to take pre-emptive action in the drug development process to minimize the costs and time delays associated with that specific effect.
A different approach, using a new method of drug discovery.
The AIBioPharma Solution combines current and historical data to forecast drug effects on human body, allowing for tactical deployment of a pharmaceutical company's resources to take preventative action rather than wasting significant resources and effort "cleaning-up" and dealing with an existing issue.
This predictive platform has the potential to drastically cut costs, risks, and time spent on medication development.
By predicting drug effects and safety earlier, costly and time-consuming drug development processes can be avoided.