 |
| In Silico Clinical Trials Market |
The in silico clinical trials market is estimated to be valued at US$ 3,410.4 Mn in 2023 and is expected to exhibit a CAGR of 7.9% over the forecast period 2023 to 2030, as highlighted in a new report published by Coherent Market Insights.
Market Overview:
In silico clinical trials refer to the use of computer simulation to predict
drug efficacy and toxicity. It helps perform clinical trials computationally
before testing drugs on humans. Key applications include predicting human
physiology and disease progression, drug metabolism and kinetics, biomarker
analysis, and population variability analysis. In silico trials help reduce
time and costs required for drug development by replacing animal and early phase
human testing.
Market Dynamics:
Growing focus on reducing costs associated with drug development is a key
driver for the in silico clinical trials market. Conventional clinical trials
involve significant financial investments over long durations. In silico
methods offer a cost-effective alternative by computational modeling of drug
behavior without needing physical human or animal testing. For example, Abzena
Ltd. uses Bayesian modeling for in silico prediction of drug metabolism and
toxicology, helping pharmaceutical firms cut development costs by 30-50%.
Growing popularity of personalized medicine is another factor fueling market
growth. In silico trials facilitate personalized healthcare approaches by
enabling simulation of individual patient profiles through integration of
biomarker data and human genome sequences. This helps determine drug efficacy
and safety for specific patient populations upfront.
SWOT Analysis
Strength: In Silico Clinical Trials have several advantages over traditional
clinical trials. They can reduce the time and costs associated with drug
development significantly. In silico trials allow experiments to be conducted
rapidly and inexpensively in a controlled virtual environment. They can screen
thousands of potential drug candidates in a very short period of time.
Weakness: Existing computational methods and models still have limitations and
may not fully replicate complex human biology. Accurately simulating human
physiology and predicting potential adverse drug reactions in silico is
challenging. There is a lack of standardized protocols and processes for
conducting virtual clinical trials.
Opportunity: In silico clinical trials can help address the problems of high
costs and risks associated with drug development. They provide an ethical
alternative to animal testing. Advancements in AI, machine learning and
computing power are enhancing the capabilities of virtual clinical trials.
Threats: Reluctance among pharma companies to fully replace animal and human
testing with virtual approaches poses a threat. Physicians and regulators may
not fully trust results from virtual trials and still require some level of
physical validation.
Key Takeaways:
The global In
Silico Clinical Trials Market Growth is expected to witness high
growth, exhibiting CAGR of 7.9% over
the forecast period, due to increasing R&D investments made by
pharmaceutical companies in developing virtual trial platforms. adoption of
virtual trials is expected to reduce costs associated with drug development by
50–70%.
Regional analysis: North America dominated the global market in 2022 attributed
to presence of key players and growing investments for research in the region.
Europe and Asia Pacific are expected to exhibit lucrative growth owing to
increasing government funding for startups working on virtual clinical trials.
Key players operating in the In Silico Clinical Trials market are Abzena Ltd.,
Clarivate, Immunetrics Inc., GNS Healthcare, Dassault Systemes, Evotec,
Novadiscovery, Insilico Medicine Inc., and InSilicoTrials Technologies, among
others. Key players are focussing on expanding their virtual trial platforms
through partnerships and strategic collaborations.
Read More,
https://www.trendingwebwire.com/in-silico-clinical-trials-market-trends-size-and-share-analysis/
0 Comments