Computer-generated "synthetic contingency" plans at times of logistics and supply problems: scenarios for hydroxychloroquine and remdesivir

Process Development for the Manufacture of the Antimalarial Amodiaquine Dihydrochloride Dihydrate

A robust process for the manufacture of the active pharmaceutical ingredient (API) amodiaquine dihydrochloride dihydrate (ADQ, 3), an important antimalarial, is reported. The process consists of a three-step synthetic route that involves a Mannich reaction, substitution with 4,7-dichloroquinoline (4,7-DCQ, 5), and rehydration. Additionally, a cost-competitive process for the production of 4,7-DCQ (5) is also reported wherein 4,7-DCQ (5) was prepared in four steps from meta-chloroaniline (7). 4-Acetamido-2-(diethylaminomethyl)phenol (14), 4,7-DCQ (5), and ADQ (3) were obtained in yields of 92, 89, and 90%, respectively. Costing and process mass intensities of 4,7-DCQ and ADQ are also reported.

Optimized synthesis of anti-COVID-19 drugs aided by retrosynthesis software

Considering the millions of COVID-19 patients worldwide, a global critical challenge of low-cost and efficient anti-COVID-19 drug production has emerged. Favipiravir is one of the potential anti-COVID-19 drugs, but its original synthetic route with 7 harsh steps gives a low product yield (0.8%) and has a high cost ($68 per g). Herein, we demonstrated a low-cost and efficient synthesis route for favipiravir designed using improved retrosynthesis software, which involves only 3 steps under safe and near-ambient air conditions. A yield of 32% and cost of $1.54 per g were achieved by this synthetic route. We also used the same strategy to optimize the synthesis of sabizabulin. We anticipate that these synthetic routes will contribute to the prevention and treatment of COVID-19.

Reinforcing the supply chain of umifenovir and other antiviral drugs with retrosynthetic software

The global disruption caused by the 2020 coronavirus pandemic stressed the supply chain of many products, including pharmaceuticals. Multiple drug repurposing studies for COVID-19 are now underway. If a winning therapeutic emerges, it is unlikely that the existing inventory of the medicine, or even the chemical raw materials needed to synthesize it, will be available in the quantities required. Here, we utilize retrosynthetic software to arrive at alternate chemical supply chains for the antiviral drug umifenovir, as well as eleven other antiviral and anti-inflammatory drugs. We have experimentally validated four routes to umifenovir and one route to bromhexine. In one route to umifenovir the software invokes conversion of six C–H bonds into C–C bonds or functional groups. The strategy we apply of excluding known starting materials from search results can be used to identify distinct starting materials, for instance to relieve stress on existing supply chains.

COVID-19 has exposed the fragility of supply chains, particularly for goods that are essential or may suddenly become essential, such as repurposed pharmaceuticals. Here the authors develop a methodology to provide routes to pharmaceutical targets that allow low-supply starting materials or intermediates to be avoided, with representative pathways validated experimentally.

COVID-19 into Chemical Science Perspective: Chemical Preventive Measures and Drug Development

COVID-19 facts and literature are discussed into chemical science intuition highlighting the direct role of chemistry to the ongoing global pandemic by covering structural identification of the virus, chemical preventive measures and development of drugs. We reviewed the four most promising repurposed drugs which are presently being investigated in mass clinical trials on COVID-19 infected persons and synthetic routes of these drugs with their recent advancement. Chemical preventive measures such as soap water, hand sanitizer and disinfectant are the only available options in the arsenal to fight against COVID-19, till an effective medicine or vaccine will be made available. As such the present review will focus on the mode of action of the major chemical preventives.

Chemist Ex Machina: Advanced Synthesis Planning by Computers

Teaching computers to plan multistep syntheses of arbitrary target molecules-including natural products-has been one of the oldest challenges in chemistry, dating back to the 1960s. This Account recapitulates two decades of our group's work on the software platform called Chematica, which very recently achieved this long-sought objective and has been shown capable of planning synthetic routes to complex natural products, several of which were validated in the laboratory.For the machine to plan syntheses at an expert level, it must know the rules describing chemical reactions and use these rules to expand and search the networks of synthetic options. The rules must be of high quality: They must delineate accurately the scope of admissible substituents, capture all relevant stereochemical information, detect potential reactivity conflicts, and protection requirements. They should yield only those synthons that are chemically stable and energetically allowed (e.g., not too strained) and should be able to extrapolate beyond examples already published in the literature. In parallel, the network-search algorithms must be able to assign meaningful scores to the sets of synthons they encounter, make judicious choices which of the network's branches to expand, and when to withdraw from unpromising ones. They must be able to strategize over multiple steps to resolve intermittent reactivity conflicts, exchange functional groups, or overcome local maxima of molecular complexity.Meeting all these requirements makes the problem of computer-driven retrosynthesis very multifaceted, combining expert and AI approaches further supplemented by quantum-mechanical and molecular-mechanics calculations. Development of Chematica has been a very long and gradual process because all these components are needed. Any shortcuts-for example, reliance on only expert or only data-based approaches-yield chemically naïve and often erroneous syntheses, especially for complex targets. On the bright side, once all the requisite algorithms are implemented-as they now are-they not only streamline conventional synthetic planning but also enable completely new modalities that would challenge any human chemist, for example, synthesis with multiple constraints imposed simultaneously or library-wide syntheses in which the machine constructs "global plans" leading to multiple targets and benefiting from the use of common intermediates. These types of analyses will have profound impact on the practice of chemical industry, designing more economical, more green, and less hazardous pathways.