Life-sciences & Pharmaceuticals Industry

Improving time & cost efficiencies in R&D

The Problem: R&D is an arduous, time consuming and expensive process
which requires a lot of complex analysis based on multiple data points and is highly dependent on the abilities of individual research analysts.


Our Proposed Solution: Using AI in lab equipment to automate portions of
experiments by identifying vision based characteristics and suggesting next steps, auto-complete findings, and suggest conclusions. Voice based AI such as Alexa can be trained with specific data scraped from various sources on the world wide web to assist in labs. Collecting and analyzing data and using Machine Learning to identify patterns will reveal insights in lab experiments and aid research and new product development.


ROI: Accelerated R&D resulting in reduced costs, higher accuracy and better products. Ability to identify new patterns and insights that humans may miss.

Assisting in Clinical Trials

The Problem: Clinical trials is an inaccurate science prone to attrition and and can be time consuming and expensive.


Our Proposed Solution: AI can aid researchers in patient selection by choosing patients who are more likely to have a measurable clinical endpoint and identifying a population more capable of responding to treatment. This can be further extended by proactively searching
EHR records to scout eligible patients. AI can help monitor patient behavior thru clinical trials and detect signs of patient dropout and take measures to prevent possible dropouts.Voice enabled AI health assistant connected to IoT devices such as mobile phones, smart watches and other wearables for helping patients adhere to trial protocols.

ROI: Increased accuracy in patient selection. Fewer dropouts and better adherence to trial pro-
tocols.

AI in Quality Control

The Problem: Quality control and health & safety is a critical element of the

pharmaceutical industry. Due to the high cost of quality testing, today most companies use manual supervision and random product sampling techniques to monitor product quality and ensure health & safety. However the cost of any errors is extremely high and could be catastrophic for a company in this industry.


Our Proposed Solution: Using spectrogram analysis and computer vision checks at every stage of the manufacturing process, we can ensure ingredient quality is checked at every stage, all correct manufacturing procedures are followed and all health and safety standards for both machinery and workers are met. This will enable pharmaceutical manufacturers to reduce reliance on manual supervision and
random sampling thereby assuring quality with a higher degree of confidence.


ROI: Increased product quality and higher customer satisfaction. Lower health & safety risks. Reduced labour costs. Eliminate high cost
of product recalls, or damage caused to the brand equity.