AI is becoming an increasingly powerful tool for pharmaceutical businesses, and this technology has many applications. Help pharmaceutical businesses find the best candidates for clinical trials and reduce friction in bringing new drugs to market.
AI Cohort Builder tool.
Clinical AI and pharmacy intelligence software from DocStation that applies machine learning and NLP to medical data. It analyzes unstructured and structured data, extracting tens of thousands of data points. Its algorithms analyze data in the context of patient-clinical trial matching and create multidimensional patient profiles.
The Cohort Builder feature allows researchers to filter their datasets by document type, reducing the number of false positives. In addition, the system recognizes partial matches and negations. It can even filter by Boolean operator and calendar icon, reducing the risk of false positives. In addition, it has a multi-filtering feature to identify patients with a specific medical condition or disease.
Natural language processing.
For years, humans have struggled to understand the complexities of the inclusion criteria used in clinical trials. Until recently, humans were the only ones who could understand the data, but computers can understand free text data with the advancement of AI. With Antidote, computers can interpret unstructured text data and recommend studies based on their answers. As a result, Eighty-six percent of clinical trials fail to recruit enough patients, a problem that delays research and delays patient access to life-saving drugs.
In a recent study, researchers at the Highlands Oncology Group evaluated an automated clinical trial matching system using machine learning and natural language processing to match cancer patients with fair trials. They analyzed the eligibility criteria of 997 breast cancer patients, comparing the system’s performance with that of a human reviewer. The results revealed that the system’s eligibility determinations were more specific and sensitive and took less than a third of the time.
Drug Adherence Tracking.
An AI-driven clinical app uses facial recognition technology to track how well patients take their medications. It also uses camera technology on a mobile device to monitor the environment. In addition to adherence monitoring, its AI-powered platform can flag adverse events and monitor patient symptom reporting to help healthcare providers better tailor care.
One way to measure drug adherence is to count pills. However, if a patient isn’t taking their medications properly, data from the trial will be erratic. Videotaping a patient swallowing a pill can improve data accuracy by 90 percent. While medication containers can record when and how a patient takes a medication, it is difficult to measure the amount of pill intake. Direct observation of a patient is expensive and invasive, and self-reporting is imprecise. The software helps solve these challenges and improves drug adherence.
Another AI and pharmacy intelligence company is tackling the problem of medication adherence by using social network activity recognition. Its patent covers a method and apparatus connecting social networks to post updates to users’ profiles automatically. This approach may be applied to tracking the adherence of chronically ill patients.
Pharmacies using AI-powered technology.
As the health care value chain experiences exponential change, pharmacists’ role will evolve dramatically. As we move from fee-for-service reimbursement to value-based care, the role of a pharmacist will likely change, too. First, this article will discuss some of the benefits of AI in pharmacy operations. Then, we’ll look at how AI will change the practice of community pharmacists. In addition, learn how AI-powered technologies will improve workflow and improve decision-making for community pharmacists.
The adoption of AI-powered pharmacy automation is already beginning in community pharmacies. For example, over 70 percent of Denmark’s community pharmacies have implemented automated dispensing technology. This technology can help pharmacists save time while dispensing prescriptions and labelling them accurately. It can also reduce errors and rework in a pharmacy. By 2025, the global AI market will reach $89.8 billion.
