Introduction: The drugs approved by the Food and Drug Administration (FDA) in 2022, for the first time for any indication or under any brand, were studied under the contexts of indications, mechanism of action, and side effects. Primary care practitioners with considering patients as a composite whole will benefit by acquainting themselves with these drugs and their indications and adverse effects.
Observations: The drugs were approved in all, 11 for the management of neoplasia, and 5 each for hematological, neurological, and dermatological conditions. 11 of the approved drugs are monoclonal antibodies and six are small molecule inhibitors.
Conclusion: Although the FDA's expedited approval program allows rapid market availability of drugs for difficult to treat conditions, a quarter of the globe does not have access to essential medicines, primarily due to cost. In light of this, approval agencies must reorient approval processes to improve accessibility.
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http://dx.doi.org/10.4103/jfmpc.jfmpc_188_23 | DOI Listing |
EClinicalMedicine
October 2024
Department of Oncology, Queen's University, Kingston, Canada.
Patients with cancer expect prolonged life (overall survival, OS) or better life (quality of life, QOL) from cancer treatments. However, majority of new cancer drugs are now being approved not based on improved OS or QOL, but based on surrogate endpoints such as tumor shrinkage or delayed tumor progression. These surrogate endpoints, including their validity as a proxy for overall survival, differ based on disease settings and lines of treatment but in general, most surrogate measures have weak correlation with outcomes that matter to patients.
View Article and Find Full Text PDFHealth Inf Sci Syst
December 2025
Division of Software, Yonsei University, Mirae Campus, Yeonsedae-gil 1, Wonju-si, 26493 Gangwon-do Korea.
Purpose: Drug repositioning, a strategy that repurposes already-approved drugs for novel therapeutic applications, provides a faster and more cost-effective alternative to traditional drug discovery. Network-based models have been adopted by many computational methodologies, especially those that use graph neural networks to predict drug-disease associations. However, these techniques frequently overlook the quality of the input network, which is a critical factor for achieving accurate predictions.
View Article and Find Full Text PDFDrugs must accumulate at their target site to be effective, and inadequate uptake of drugs is a substantial barrier to the design of potent therapies. This is particularly true in the development of antibiotics, as bacteria possess numerous barriers to prevent chemical uptake. Designing compounds that circumvent bacterial barriers and accumulate to high levels in cells could dramatically improve the success rate of antibiotic candidates.
View Article and Find Full Text PDFBenchmarking is an important step in the improvement, assessment, and comparison of the performance of drug discovery platforms and technologies. We revised the existing benchmarking protocols in our Computational Analysis of Novel Drug Opportunities (CANDO) multiscale therapeutic discovery platform to improve utility and performance. We optimized multiple parameters used in drug candidate prediction and assessment with these updated benchmarking protocols.
View Article and Find Full Text PDFTargeted kinase inhibitors are well known for their promiscuity and off-target effects. Herein, we define an off-target effect in which several clinical BRAF inhibitors, including the widely used dabrafenib and encorafenib, interact directly with GCN2 to activate the Integrated Stress Response and ATF4. Blocking this off-target effect by co-drugging with a GCN2 inhibitor in A375 melanoma cells causes enhancement rather than suppression of cancer cell outgrowth, suggesting that the off-target activation of GCN2 is detrimental to these cells.
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