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Dear Readers,Welcome to the latest issue of Microb
Drug discovery is an ever-evolving field of research, branching out into numerous novel routes such as immunotherapies and gene therapy. At this forefront of development, scientists face a host of drug discovery challenges that hinder progress. It is vital that the industry takes steps to reduce costs and increase discovery efficacy for more financially and medically successful research in the future.
Challenges such as rising costs, modeling limitations, and misunderstood underlying disease mechanisms stand in the way of more effective drug discovery. As research pushes forward into new modeling technologies, we can ask: how is the industry attempting to tackle these challenges? Are the current efforts successful?
Drug discovery is a broad area of research encompassing many different disciplines. Identifying new drug candidates often requires teams of interdisciplinary researchers to pool their expertise and approach the problem from multiple angles. When we think about the challenges of drug discovery, we are identifying challenges faced by many different key players. Moreover, the therapeutics landscape is now so diverse that these key players differ depending on the type of drug being developed, as each class requires specific expertise.
Challenges can trickle down to all the industries involved with drug discovery and affect the entire landscape, making it a wide-reaching problem with many implications.
Drug discovery is a risky investment. It is estimated that fewer than 14% of all drug candidates entering phase 1 clinical trials (the first human trial) gain FDA approval, and the successful ones take, on average, 10-15 years and a $2.5 billion investment to get there. Research and development spending has increased without the number of approved drugs increasing at the same rate, meaning that higher investment per approved drug is needed each year.
Financial drug discovery challenges can be tackled using a multipronged approach to address all these factors simultaneously. Ideally, the industry can increase the efficacy of its modelling technologies, which can provide a better in-depth understanding of underlying disease mechanisms and more accurate identification of potential drug targets.
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