Despite high expectations, productivity is frustratingly low in biopharmaceutical research and development. Although expenditures have increased, the number of new medicines resulting from human-genome sequencing has not. This means that a broad variety of diseases are not being treated effectively, in the developed or the developing worlds.
Advances in molecular sciences, corresponding to the sequencing of the human genome in the 1980s, led to the identification of all the human proteins — large, complex molecules necessary for many of the body’s functions. Understanding the proteins’ roles then led to greater knowledge of the underlying causes of diseases. For example, mutations, or defects, at specific molecular locations in human DNA were found to be responsible for some cancers, raising the hope of developing successful therapies tailored to individual patients.
Scientists believed that the ability to visualize and understand human biology at a more detailed level would lead to many new medicines. Identifying the defective molecular parts, known as the drug targets, should have made addressing the causes of disease easier, and would revolutionize the pharmaceutical sciences. And so it has — but without increasing the number of new medicines.
Prior to this molecular revolution, scientists discovered medicines by randomly evaluating different chemicals against phenotypes — an organism’s observable characteristics — in authentic biological systems, such as animals or cells. However, unfortunately, the phenotypic strategy is neither efficient nor intellectually satisfying.
The molecular revolution heralded an era in which drug discovery and development would be rational, not random. However, contrary to expectations, the increased efficiency implied by target identification has not increased productivity. Efforts to address the problem have focused on how the target was selected, the candidate drugs’ efficacy in humans, the risk of undesirable side effects and the efficiency of the discovery process — all to little or no avail.
The July issue of Nature Reviews Drug Discovery analyzed how first-in-class medicines — those drugs that successfully established a new class of medicines — were discovered. Despite the emphasis on target-based drug discovery, phenotypic screening produced the lion’s share of the first-in-class small-molecule medicines approved between 1999 and 2008 — 28 phenotypic medicines versus 17 target-based drugs. Considering how strongly biased the industry has been toward target-based drug discovery, that imbalance is highly significant.
The Nature Reviews article proposed that lower productivity partly reflects target-based discovery’s lack of consideration of the molecular complexities of how the drugs work. Knowing the parts of an efficient machine — a watch, an automobile or a computer — is not enough to describe how it works. The parts must collaborate in precise ways to provide accurate time, reliable transportation or processed information.
Biology is infinitely more complex. The phrase “molecular mechanism of action” (MMOA) describes the way that biological parts collaborate to provide an effective and safe medicine. Addressing the MMOA would contribute to reversing the low productivity of target-based discoveries, because merely knowing the identity of a part involved in a defect may not be sufficient to repair a malfunctioning machine.
The target-based approach is analogous to looking for one’s keys in the dark: If they are under a streetlight, they will be easy to find. Many hoped that the molecular revolution would amount to more streetlights for drug discovery. Unfortunately, it appears that this new light, in most cases, is too dim to illuminate the molecular details of the dynamic human biological machine with sufficient specificity to rationalize the design of new medicines.
The random phenotypic process, though less efficient, will ultimately identify medicines that are effective and work to repair disease. The target-based approach, on the other hand, creates only the illusion of greater efficiency; in reality, its promise has been undermined by its inattention to the MMOA.
There are too many molecular possibilities in dynamic human biology to identify a priori the optimal mechanism of molecular intervention. The way forward is to find a method that combines the efficiency of target-based approaches with the authenticity of phenotypic research.
David Swinney is at the Institute for Rare and Neglected Diseases Drug Discovery and was previously director of Virology Biochemical Pharmacology at Roche, Palo Alto, California.
Copyright: Project Syndicate
A chip made by Taiwan Semiconductor Manufacturing Co (TSMC) was found on a Huawei Technologies Co artificial intelligence (AI) processor, indicating a possible breach of US export restrictions that have been in place since 2019 on sensitive tech to the Chinese firm and others. The incident has triggered significant concern in the IT industry, as it appears that proxy buyers are acting on behalf of restricted Chinese companies to bypass the US rules, which are intended to protect its national security. Canada-based research firm TechInsights conducted a die analysis of the Huawei Ascend 910B AI Trainer, releasing its findings on Oct.
In honor of President Jimmy Carter’s 100th birthday, my longtime friend and colleague John Tkacik wrote an excellent op-ed reassessing Carter’s derecognition of Taipei. But I would like to add my own thoughts on this often-misunderstood president. During Carter’s single term as president of the United States from 1977 to 1981, despite numerous foreign policy and domestic challenges, he is widely recognized for brokering the historic 1978 Camp David Accords that ended the state of war between Egypt and Israel after more than three decades of hostilities. It is considered one of the most significant diplomatic achievements of the 20th century.
As the war in Burma stretches into its 76th year, China continues to play both sides. Beijing backs the junta, which seized power in the 2021 coup, while also funding some of the resistance groups fighting the regime. Some suggest that Chinese President Xi Jinping (習近平) is hedging his bets, positioning China to side with the victors regardless of the outcome. However, a more accurate explanation is that China is acting pragmatically to safeguard its investments and ensure the steady flow of natural resources and energy for its economy. China’s primary interest is stability and supporting the junta initially seemed like the best
Numerous expert analyses characterize today’s US presidential election as a risk for Taiwan, given that the two major candidates, US Vice President Kamala Harris and former US president Donald Trump, are perceived to possess divergent foreign policy perspectives. If Harris is elected, many presume that the US would maintain its existing relationship with Taiwan, as established through the American Institute in Taiwan, and would continue to sell Taiwan weapons and equipment to help it defend itself against China. Under the administration of US President Joe Biden, whose political views Harris shares, the US on Oct. 25 authorized arms transfers to Taiwan, another