The pharmaceutical business has one of the most complicated business structures, where to get the product from idea to market medical institutions need to spend about a decade, several billion dollars, and there is about a 90% chance of failure.

•       For instance, a company called Antidote, is matching patients and medical researchers in clinical trials so they could work together more easily. The platform allows patients to find the most suitable clinical trials, helps researchers stream their latest study information to millions of patients, and even connects them with members of the medical community directly.

•       Another example is Atomwise. The most recognized company in drug discovery aims to reduce the costs of medicine development by employing data and computers to predict molecular structures in advance which potential medicines will work, and which won’t. The AtomNet neural network screens more than hundred million compounds each day.

AI Can Push Innovation And Progress Further

The pharmaceutical industry has lagged in accepting emerging technology. Hence, incorporating AI technology early can push innovation and progress further. Furthermore, having more of a grasp of AI can change the culture around adopting such technology.

As Andrew McAfee and Erik Brynjolfsson, MIT economists, state “So we should ask ‘What do we want to do with technology?’ More than ever before, what matters is thinking deeply about what we want. Having more power and more choices means that our values are more important than ever.”

The pharmaceutical business has one of the most complicated business structures, where to get the product from idea to market medical institutions need to spend about a decade, several billion dollars, and there is about a 90% chance of failure.

Therefore, many pharmaceutical businesses started investing heavily in R&D, and internal data centres but without a coherent strategy these re-branding exercises resulted in many heads of data, artificial intelligence, digital, in one corporation and often in one division. While some of the pharmaceutical companies advanced their digital initiatives, no sizable acquisitions were made to date.

Pharmaceutical industries have to develop more data science and digital competencies to transform their R&D model to become “digital pharma players”.

Today’s questions for health facilities are:

•       Develop an AI-powered R&D strategy

•       Become “digital pharma player” to fully leverage the potential of technology

•       How to manage the transformation?

According to a recent United Nations report, by 2050, one in five people in Europe and America will be over the age of 65 — this means the health systems will have to deal with more patients with complex needs. Working with such patients is expensive and requires technology to automate and shift care-based philosophy to a more efficient long-term care management.

How To Revolutionize Healthcare With Artificial Intelligence (AI)?

AI can advance care outcomes and systematize the process of care delivery. It can foster innovation in life-saving treatments and lead to an improvement in the daily life of healthcare specialists, letting them to focus more on after-care, raise staff self-esteem and improve wellbeing. Artificial intelligence ‘know-hows’ promise to speed up the process of drug discovery and make it more cost-cutting.

Today, more than 78 per cent of the recently patented medications approved by the USDA correspond to drugs already on the market, according to the Washington Post article. Big Pharma companies are rebranding and redistributing the same medications frequently to make a profit, without bringing any new, innovative drugs to market.

Thankfully, they are companies and technologies who want to change the current situation. More and more companies started to employ AI technology that helps synthesize a lot of data and information, including the grounds of the disease, data gathering, drugs design, enabling run of preclinical experiments and clinical trials.

More companies started to employ AI technology that helps synthesize a lot of data and information, including the grounds of the disease, data gathering, drugs design, enabling run of preclinical experiments and clinical trials.

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