Category: Drug Discovery

Artificial Intelligence in Drug Discovery – Could help Reduce Significant Capital and Time Required

Drug discovery is a complex process which involves significant utilization of time and resources. As per several sources, on an average, the entire drug development process (from initial proof-of-concept to commercial launch) takes around 10-15 years and capital investments worth USD 4-10 billion to develop a drug from concept to commercial launch. The early stages

Advancing Healthcare Delivery via Artificial Intelligence

Artificial Intelligence have demonstrated intelligent behavior through their ability to learn, communicate with its users and solve complex problems using highly sophisticated algorithms. AI-driven technologies have continued to evolve rapidly, with several industries increasingly deploying such solutions across key aspects of value chain. Furthermore, AI is also made with same idea of making tasks simpler

Increasing Rate of Drug Failure has Prompted the Drug Developers to Rely on CROs offering In Vitro ADME Testing Services for their Outsourcing Requirements

It is important to note that the process of drug discovery is extremely demanding, both in terms of capital and time. In fact, the overall amount spent on R&D initiatives in the pharmaceutical / biotechnology sector has increased from around USD 128 billion in 2008 to USD 165 billion in 2018. Moreover, only a small

Targeted Protein Degradation – Defining a New Frontier in the Field of Medicine

The concept of targeted protein degradation presents revolutionary drug development opportunities and is anticipated to bring about a paradigm shift in modern healthcare. While conventional medicines, such as small molecule inhibitors and monoclonal antibodies, address fewer than 20% of the proteome, targeted protein degradation offers a unique means to tap into the rest of the

In Silico / Computer-Aided Drug Discovery Service Providers for Large Molecules

Over time, the complexities associated with drug discovery have increased, especially in case of large molecule drugs, which are inherently more complex than conventional small molecules. As a result, an increase in the overall research and development (R&D) expenditure in the pharmaceutical / biotechnology sector has been witnessed. In addition to the complexities involved, the

Computational / In Silico Drug Discovery: A Boon in Disguise for Faster Drug Discovery Operations Amidst COVID-19

The COVID-19 pandemic is predicted to throw the global economy into recession, with loss of trillions of dollars. The pharmaceutical industry cannot escape the brunt of the circumstances as well. In fact, according to a survey, 95% of healthcare industry professionals are worried about the impact the pandemic is likely to have on the industry. So far,

Fragment-based Drug Discovery – A Boon in Disguise to get a Breakthrough Drug Against Covid-19

With over 855,000 cases and 42,000 deaths, the novel coronavirus has taken its toll on humanity. The pandemic is predicted to throw the global economy into recession, with loss of trillions of dollars. The pharmaceutical industry cannot escape the brunt of the circumstances as well. In fact, according to a survey, 95% of healthcare industry

Is genomics revolution all fun and games? How blockchain can calm data security nerves!

Have you had your genomics sequenced? If you asked this question a few years ago, people would have thought you were crazy. However, today, genetic tests are up for sale in supermarkets! Fifteen years ago, the first ever Human Genome Project was carried out, which took more than 13 years to complete. This (Human Genome

Deep Learning: Opportunities in Drug Discovery and Diagnostics

Deep learning is a novel machine learning technique that can be used to generate relevant insights from large volumes of data. The applications of the technology are being explored across a variety of areas. The ‘Deep Learning: Drug Discovery and Diagnostics Market, 2017-2035′ report examines the current landscape and future outlook of the growing market of deep learning