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The Latest Enhanced Technology For Faster Medical Trials

The Latest Enhanced Technology For Faster Medical Trials

Technology is evolving every day, and as such, it’s helping the medical sector speed up its trial processes. Want to find out how? Then give this a read.

Medical Trials Over in A Flash

New drug testing is a time-consuming and costly process. Technology can disrupt clinical trials from patient recruiting to adherence tracking and data collection, and Covid-19 has accelerated its use. Nearly 5,000 clinical trials conducted by companies such as Clinical Ink have been launched in the last year to investigate life-saving therapies and vaccinations for the new coronavirus.

It takes a long time and a lot of effort to bring a medicine to market. According to studies, the clinical trial procedure — in which new pharmaceuticals are tested on patients before being approved — takes an average of 9 years and costs $1.3 billion. Clinical trials are carried out in stages, with the expense and complexity growing as the trial progresses from Phase I through Phase III. Despite the time and money spent on studies, just one out of every ten medications that enter Phase I will be approved. Therefore, these trials must be completed as swiftly as possible. But of course, this can not come at the detriment of the trial itself.

With this in mind, we decided to investigate the technologies that can help speed up these processes and, as a result, benefit the medical healthcare industry.

Artificial Intelligence

 Artificial intelligence-powered technology can revolutionize the clinical trial process, from discovering a study through enrollment to medication adherence. Matching the right trial to the right patient, on the other hand, is a time-consuming and difficult endeavor for both the clinical study team and the patient. On rare occasions, patients may receive trial recommendations from their doctors if they are aware of an ongoing trial. Otherwise, it is frequently the patient’s responsibility to search through clinical trials and a complete database of historical and ongoing clinical trials.

Natural language processing can help extract and evaluate essential information from a patient’s EHR records, compare it to trial eligibility criteria, and select studies that are a good fit. One of the most sought-after artificial intelligence applications in healthcare is collecting information from medical records.

The design of clinical trials is another area where AI is being used. Every clinical trial has a protocol that outlines how the investigation will be carried out. Any issues that develop throughout the trial that necessitate protocol changes might cause months of delays and cost hundreds of thousands of dollars. Drug development is faster and less expensive when processes are followed correctly. Researchers use information from various sources while planning a trial, including comparative studies, clinical data, and regulatory information. Not only can AI-powered software handle all of that data faster, but it can also collect more data than a human can read.

Safety Monitoring 

As digital technology becomes more incorporated into normal clinical trial processes, researchers are increasingly integrating novel technologies with existing biomarker analyses to prove their safety and utility. Using digital technology to gather data in real-time and send it to researchers could aid researchers in detecting infrequent or situation-specific events that are unlikely to occur during a study visit. The speed with which adverse and safety events are identified and reported could have a significant impact on the completion and documentation of clinical studies.

Quantum Computing

While using computational approaches to identify drugs isn’t new, using ultra-efficient quantum computers to uncover previously unknown molecules has only lately surfaced as a promising topic. While traditional computers employ “bits” that are either on or off, quantum computers use “qubits” that can be on, off, or both – a phenomenon known as superposition. Because of this superposition property, quantum computers may substantially speed up and improve testing and predictions, making the technology particularly attractive for drug development.

While quantum computing is still in its infancy, industry participants have recognized its potential to revolutionize medical research – and the pharma sector isn’t waiting to get involved, as evidenced by a flurry of collaborations struck this year between small groups and large drug corporations.

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