New York City, New York Oct 4, 2021 (Issuewire.com) - 10 tendencies that make present-day technologies irreplaceable.
Modern healthcare largely depends on the effectiveness of clinical trials. This has become especially evident in the past two years, as the world faced the COVID-19 pandemic and the need to find the right medicines and develop vaccines as fast as possible. Less than a year has passed between the moment the first patient was diagnosed with a new virus in China and the moment the first vaccine got its license — a record time for the global pharmaceutical industry.
However, this seems to be just the tip of the iceberg: advanced information technologies are revolutionizing clinical trials, so the scientific system itself is expected to undergo breakthrough changes within the next decade.
10 main trends
- More trials and errors
Artificial intelligence enables testing numerous promising medications in silico, i.e., using computer modeling. At its present stage of development, the in silico method cannot substitute classical trials with human and animal testing. But it is able, for example, to prescreen the efficacy of a targeted drug without losing time on searching for candidates.
- A search for candidates becomes more effective
Until recently, many leaders of research teams had no opportunity to facilitate their search for candidates and 86% of clinical trials had to be delayed globally. Nowadays, this opportunity is given to them by artificial intelligence that can find the right candidates in a few seconds and even send them standard invitation letters. This is probably the most obvious part of all the work delegated by us to the machines.
- Openness to everyone
My colleagues from DQueST designed a smart survey that helps candidates to filter out clinical trials that are clearly not applicable to them. It takes only 50 simple questions to cross out 60-80% of trials, lowering the threshold for those interested in participation.
- Protocol design gets better
Services like Trials.ai can collect all data on previous and current research from available open sources so it could be used for designing a trial protocol.
- Monitoring at all stages
. Nowadays, there are platforms that not only remind patients to take their medicine but also analyze its administering via smartphone cameras and computer vision. Further development of artificial intelligence, including facial, speech, and emotion recognition, as well as “smart” gadgets that can measure multiple parameters will increase the efficiency of participation control and make trial results more accurate.
- NLP: systematization becomes easier
Another promising trend is natural language processing (NLP). NLP systems help the computer to analyze written and verbal texts. In the case of medicine and clinical trials, their main objective is to find relevant excerpts from medical charts and records made by doctors and patients themselves — even including words uttered during a check-up.
- A quick analysis of collected data
Nowadays, any large-scale research can be quickly converted into elegant charts, tables, and mathematical models. And thanks to these technologies, for the first time ever mankind has the opportunity to literally observe the spread of a new virus online.
- Prospects of making a universal database
The next step of big data development is a single database for all healthcare systems, patients, doctors, and studies in the world. Overcoming language barriers and national borders, this database would become the cornerstone of future medical progress.
- Double-blind, randomized, placebo-controlled clinical trials: a relic of the past?
Medicine can also eventually introduced so-called “virtual patients”. As of now, such technologies are used primarily for medical education, yet it is possible to create a digital “human model” to test the efficacy of various medications.
- Lower expenses on trials, higher revenues for pharma companies
Artificial intelligence itself cannot replace a human being at the helm of a clinical trial or real patients taking part in the research, but it could save these billions. I truly hope that the funds saved by IT will be spent by pharmaceutical companies on developing new drugs, vaccines, and therapy methods. For us, investors and IT specialists, this is both important and inspiring.
About the Author
Rustam Gilfanov is an IT entrepreneur and a venture partner of the LongeVC Fund.
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