In recent years, the pharmaceutical industry has opened itself up to the idea of new technologies that will help improve the current practices in place.
One of these technologies is artificial technology, which refers to a system of interconnected and automated technologies in the biotech industry.
The point of artificial intelligence in pharma is that is functions autonomously, with little or no intervention from humans.
Unlike other industries that have been hesitant to accept artificial intelligence, it’s crucial that the pharma industry is on board.
This is because artificial intelligence in pharma is responsible for key developments throughout the industry, covering everything from drug development right down to patient experiences.
As we continue to expand our understanding of the technology, the ability to which we will be able to improve things will only increase.
With that being said, we’re seeing phenomenal changes from artificial intelligence in pharma as early as this year, 2019.
Here is how artificial intelligence is already proving helpful to the pharma industry in 2019.
It Speeds Up The Discovery and Development of New Drugs
One of the biggest struggles in the pharma industry at the moment is drug discovery and development.
As it stands, 9 in 10 clinical drugs will fail to make it into trial stage, and even more won’t reach the point of being approved by the FDA.
Not only does this mean that a lot of time has been wasted developing drugs that will never be put into fruition, but it’s also a massive expenditure for the industry.
These costs have to be collected somewhere, and unfortunately, it’s patients who often have to foot the bill.
This has lead to steep price increases that leave many drugs inaccessible to those who need it the most, especially those who are uninsured or underinsured and cannot find cover for the medications they need.
By using machine learning and combining it with big data, however, artificial intelligence can be used to speed up the process completely, reducing the cost and wasted time in developing new drugs.
One development currently shaking up the pharma industry is a collaboration between Bayer and Cyclica.
The two companies are using AI-augmented and cloud-based platforms to improve how scientists design, screen, and customise new drugs.
This will make the process of validating drugs far easier by predetermining successful drugs through a process of elimination of specific ingredients.
Artificial Intelligence Will Help To Find Reliable Clinical Trial Patients Faster
Clinical trials provide the pharma industry with heaps of helpful data that helps create new treatments—and cures—for conditions every day.
Finding and enrolling ideal candidates within these studies isn’t an easy process, however, with the average process lasting 7.5 years.
As well as time, this is also a big way the pharma industry spends their money, with clinical trials costing between $161 million and $2 billion per drug.
The use of AI in pharma could see the average time taken and the significant cost of the process significantly reduced, however.
There are currently two companies that are using artificial intelligence to do this in America.
The first is Deep Note 6.
Using Natural Language Processing and Deep Learning, two key aspects of artificial intelligence in pharma, Deep Note 6 hopes to streamline and automate the process of clinical trial matching.
The other, Antidote, also uses Natural Learning Processing to make the exclusion and inclusion criteria in clinical studies easy.
They also incorporate the use of a few simple questions that potential patients answer on the antidote search-enable platform.
The artificial intelligence device will then deliver the patient with a list of recommended trials for them to enrol in, significantly reducing the time it takes to match a patient to a trial.
Provides The Pharma Industry With Insights Into Clinical Trial Data
Another big problem facing the pharma industry when it comes to clinical trials is how they analyse the data they receive in successful studies.
After all, when you have so much information coming in everyday, humans have to prioritize the most important things to make sure they’re making the most out of the information they’ve been provided with.
However, the development of artificial intelligence in pharma means that we are now able to analyse relevant information quickly, and in ways we couldn’t with humans.
A good example of this is Apple Researchkit, which makes it easy for people to enrol in clinical trials without having to go through physical enrolment.
This artificial intelligence technology is already being used by Duke University.
They use patient data collected by the face recognition algorithm on Apple devices to help identify autistic people.
Researchkit can also be used to make collecting the data in question easier, and to make more sense of the data that has been collected.
It Created Better Treatment and Management Options For People With Rare Diseases
With limited funds, the pharma industry has had to make some difficult decisions about where it allocates funding.
Unfortunately for the 350 million people who are suffering from 7000 different rare diseases around the world, this funding hasn’t gone to them.
At least it hadn’t until the development of artificial intelligence in pharma made things a lot cheaper, and more accessible.
These revelations have allowed companies to be provided with funds to start exploring common symptoms, which should help with diagnosing patients with rare diseases, providing them with a label that enables them to connect with others sharing their condition.
More than that, however, it also helps with creating treatments for these rare conditions once common symptoms of said conditions have been identified.
The good news is that funding has already been allocated to help people with these rare diseases to two companies around the world.
The first is Healx, a UK-based biotech firm. They have secured Series A funding for $10 million.
The other company, Entrada, is a Swiss biotech company. They have received an even more substantial fund than the aforementioned company at $59 million.This article comes from ComboApp. Check out their latest guide on How to Market your Mobile App like a Pro in 2019