AI Articles and Analysis about Research and development

Generic pharmaceuticals require less research and development than their brand name counterparts. As a result, AI applications for research and development don’t seem to be the most prominent solutions for generic drug companies. That said, despite the lack of precedence, there may be many areas in which AI could help generic drug companies.

The facilitation of research and development (R&D) is perhaps the most common use case for AI applications in the pharmaceutical industry. There are numerous solutions for extracting and organizing research data from clinical trial notes and other medical documents. Additionally, there is software that can purportedly analyze data from images of drug compounds at the molecular level.

The focus of the National Aeronautics and Space Administration (NASA) is to provide information to civilian institutions to help them solve scientific problems at home and in space. This requires a continuous stream of raw data under a constantly shifting environment.  According to a 2017 interview with Kevin Murphy, Earth Science Data Systems Program Executive at NASA, the biggest challenge now is not going where no man has gone before, but managing the data.

McKinsey estimated that embarking on digital transformation to restructure value chains and drive R&D innovation across the pharmaceutical industry could be worth $50–150 billion of earnings before interest, taxes, depreciation, and amortization. In particular, machine learning is likely to continue finding a place in the pharmaceutical industry. Pharmaceutical companies have found applications for machine learning ranging from drug discovery to clinical trial retention.
The State of AI in the Asian Pharmaceutical Industry
AI seems to be making its way into the pharmaceutical space in Asia over the last two or three years, particularly in China and Japan. For the most part, the companies offering or using AI for drug discovery are just starting to acquire funding and talent. XtalPi seems to have the highest density of talent with a decent likelihood of being able to work with machine learning.

Here at Emerj we’re dedicated to cutting through the AI hype that’s permeating the current zeitgeist in the business world. Although we’re skeptical about many of the claims that AI vendors make on their websites about what they’re AI software can do, it seems unlikely that the AI hype is going to disappoint venture capitalists and governments enough to usher in a third AI winter.

This report attempts to highlight the wide array of real-world use cases of machine vision in the military. Several militaries claim to leverage machine learning, working with contractors and companies in some cases to deliver AI solutions. We found that these solutions help highlight the wide breadth of current and near-term military applications of machine vision. The companies and organizations discussed in this report help various militaries with at least one of the following:

According to Deloitte and the Economist, global annual health spending should reach $8.734 trillion dollars by 2020, and, as mentioned in our previous report on AI for Healthcare in Asia, InkWood Research estimated the size of the artificial intelligence market in the healthcare industry at around $1.21 billion in 2016. As of now, numerous AI vendors claim to help healthcare professionals diagnose patients using machine vision. Other AI vendors claim to offer solutions for increasing adherence to drug therapy programs.

Episode Summary: One of most fun parts about doing our geolocation pieces at TechEmeergence is that we are able to interview so many people within a given country or city. Recently we did a huge piece on AI in India. We got to interview folks from the government and the bigger existing businesses, as well as a handful of people at the unicorns in Bangalore.