Drug development is costly and involves a high risk of failure during clinical trials. The transition from bench to bedside has been long, and the number of drug withdrawals has increased to historic highs. Therefore, significant investments are being made in translational research to find innovative tools that accelerate the drug discovery processes.
In the space of a few years, we have seen many technological advances across the full spectrum of the pharmaceutical industry and related technologies, such as CRISPR genome editing, machine learning and in silico modelling, that show tremendous potential to push the frontiers of pharmaceutical research to new vistas. We will see more advanced technologies infuse into the lab common practice over the next few years, and more innovative technologies will continue to emerge. It is exciting to think how drug discovery will develop in the next five years.
On the other hand, over the last decade, researchers, mainly from academia, have identified many new biological modalities and genomic variants that could be translated to new biomarkers of disease and a deeper understanding of disease progression. Unfortunately, the translation of many of these discoveries into therapeutics has not been realized due to the lack of funding or academia-industry collaboration culture. Furthermore, the fusion of many engineering disciplines, biology and medicine, allows using engineering principles to solve problems in biology and medicine, ushering in a new era of technological breakthroughs for sensing and manipulating molecules, cells, tissues, and organs.
While the high cost is considered the primary driving force in searching for other non-classical approaches to drug development, the recent (current) pandemic has revealed the importance of innovation as the best strategy in driving the healthcare industry during health crises. Most importantly, the US House of Representatives has passed the FDA Modernization Act of 2022, which eliminate the animal-testing mandate for drug development and replaces that strategy with 21st-century methods grounded on human biology. This historical policy development would reboot our drug development paradigm and moves us into a new era of drug discovery.
This research topic will highlight some intriguing possibilities for the future of drug discovery research and development that transform the traditional approaches to reduce development costs and reach patients faster, emphasizing the role of integration of engineering principles and medicine.
We invite researchers working/interested in this area to submit full-length research papers, communication, and review articles to meet the goal of this research topic.
Topics include:
1. Genomics and proteomics
2. Gene editing
3. System biology
4. Patient-centric therapeutics
5. Machine learning
6. Integration of AI into the lab automation
7. In silico modelling
8. Nanomaterial-based drug formulations
9. Novel in vitro models (e.g., organoids and organs-on-a-chip)
10. Biofabrication techniques (e.g., 3D bioprinting)
11. Process redesign
12. Academia-industry collaboration
Drug development is costly and involves a high risk of failure during clinical trials. The transition from bench to bedside has been long, and the number of drug withdrawals has increased to historic highs. Therefore, significant investments are being made in translational research to find innovative tools that accelerate the drug discovery processes.
In the space of a few years, we have seen many technological advances across the full spectrum of the pharmaceutical industry and related technologies, such as CRISPR genome editing, machine learning and in silico modelling, that show tremendous potential to push the frontiers of pharmaceutical research to new vistas. We will see more advanced technologies infuse into the lab common practice over the next few years, and more innovative technologies will continue to emerge. It is exciting to think how drug discovery will develop in the next five years.
On the other hand, over the last decade, researchers, mainly from academia, have identified many new biological modalities and genomic variants that could be translated to new biomarkers of disease and a deeper understanding of disease progression. Unfortunately, the translation of many of these discoveries into therapeutics has not been realized due to the lack of funding or academia-industry collaboration culture. Furthermore, the fusion of many engineering disciplines, biology and medicine, allows using engineering principles to solve problems in biology and medicine, ushering in a new era of technological breakthroughs for sensing and manipulating molecules, cells, tissues, and organs.
While the high cost is considered the primary driving force in searching for other non-classical approaches to drug development, the recent (current) pandemic has revealed the importance of innovation as the best strategy in driving the healthcare industry during health crises. Most importantly, the US House of Representatives has passed the FDA Modernization Act of 2022, which eliminate the animal-testing mandate for drug development and replaces that strategy with 21st-century methods grounded on human biology. This historical policy development would reboot our drug development paradigm and moves us into a new era of drug discovery.
This research topic will highlight some intriguing possibilities for the future of drug discovery research and development that transform the traditional approaches to reduce development costs and reach patients faster, emphasizing the role of integration of engineering principles and medicine.
We invite researchers working/interested in this area to submit full-length research papers, communication, and review articles to meet the goal of this research topic.
Topics include:
1. Genomics and proteomics
2. Gene editing
3. System biology
4. Patient-centric therapeutics
5. Machine learning
6. Integration of AI into the lab automation
7. In silico modelling
8. Nanomaterial-based drug formulations
9. Novel in vitro models (e.g., organoids and organs-on-a-chip)
10. Biofabrication techniques (e.g., 3D bioprinting)
11. Process redesign
12. Academia-industry collaboration
