Continuous flow techniques are increasingly being used across drug discovery, development and production to improve processes and access new chemistries that simply aren’t possible with traditional batch methods. More and more pharmaceutical chemists understand the applications of this technique, and the benefits it provides, leading to senior management at all stages of the drug lifecycle looking to continuous flow chemistry to improve reaction efficiencies, save resources and improve safety. While each stage of the drug discovery and development process will see specific benefits when implementing continuous flow techniques, the pharmaceutical industry’s desire to ultimately move towards continuous manufacturing means all stages of the drug lifecycle need to be aware of – and potentially implement – these techniques. Our focus here is on the impact, implementation, and key drivers of flow chemistry for drug discovery and how automation is helping early hit-to-lead and lead generation programs.
The medicinal chemistry and drug discovery process
Pursuing novel classes of compounds that can be used as new medicines for the treatment of diseases is not a simple task. Researchers often create new active compounds from scratch, through a laborious process involving synthesising and testing thousands of compounds with the aim of finding those suitable to be tested in human beings (1). In this context, medicinal chemistry is an interdisciplinary science at the interface of chemical biology, pharmacology and medicine, and plays a fundamental role in defining novel therapeutic approaches and the discovery of new drugs. One of the major purposes of medicinal chemistry is the design and synthesis of new lead compounds for druggable targets (2, 3). In these early stages of drug discovery, chemists aim to design and synthesise molecules with specific properties in mind. The molecules should interact with specific targets, for example, proteins suspected to cause the disease of interest. A good drug candidate should have specific physical-chemical properties, such as suitable pharmacokinetics and safety (1).
Pharmaceutical companies invest large amounts of money and time in launching a new drug to market, which can take more than a decade of research and an estimated cost of hundreds of millions of dollars (4). This process involves the synthesis and testing of tens of thousands of exploratory compounds to disclose one new drug. Figure 1 shows the average number of compounds required at each step of bringing a new drug to market over all stages of the process.
The drug discovery cycle
Medicinal chemistry is a complex process that relies on iterative learning cycles composed of molecular design, chemical synthesis, testing, and structure-activity/structure-property relationship (SAR/SPR) analysis (2). This is true for both the hit-to-lead and lead generation phases of the drug discovery process.
The selection of which series of compounds to pursue can have a huge impact on the success rates of the drug discovery process. Identifying the initial ‘hits’ showing some efficacy against the target is only the starting point, and involves screening large numbers of compounds. Once the hits are found, the iterative cycle to find one or more ‘lead’ compounds – which show improvements such as enhanced binding or pharmacokinetics – begins. These leads are then optimised using the same iterative ‘design, make, test’ cycle (Figure 2), focusing on selectivity, ADMET (absorption, distribution, metabolism, excretion, and toxicity), etc. This decision/learning cycle is critical in identifying potential drug candidates, making faster cycle rates a key factor for more efficient drug discovery. Faster iterative cycles enable faster decisions and generate leads faster.
Development of automation in the drug discovery process
Until the 1980s, information regarding biological targets, their mechanisms and their potential therapeutic applications was limited (5). Older approaches to drug discovery therefore relied on the intuitive design of compounds, which were tested in animal models, due to the lack of suitable in vitro screening methods at the time. This testing modality required resource intensive synthesis of gram quantities of each candidate compound, often resulting in the generation of just a few compounds per week, leading to long discovery timelines. The development of high throughput screening (HTS) and in vitro models over the last 30 years has enabled more efficient testing of greater numbers of compounds in a shorter time frame. This created demand for methods to synthesise compounds in larger numbers faster, leading to laboratory automation being paired with combinatorial chemistry and parallel chemistry approaches to create a huge variety of compounds to speed up the learning cycle.
The development of these automated techniques using computation modelling, high throughput experimentation and in vitro high throughput screening methods have helped to accelerate the early drug discovery process, generating large numbers of compounds for evaluation. From a medicinal chemist’s viewpoint, the synthesis of diverse compounds for screening is a key part of the drug discovery process. Chemists are therefore constantly looking for alternative solutions to increase the variety of tools in their toolboxes and solve the inherent limitations of chemical synthesis.
The adoption of enabling chemical technologies – such as laboratory automation and flow systems – have helped chemists to shorten iterative learning cycles from early discovery to production. As a result, the International Union of Pure and Applied Chemistry (IUPAC) named flow chemistry among the top 10 emerging technologies in chemistry (6) in 2019. Even more significantly, the US Food and Drug Administration (FDA) has declared continuous manufacturing (CM) to be one of the most important tools in the modernisation of the pharmaceutical industry (7).
Flow chemistry in drug discovery
The flow chemistry process enables automation and parallelisation of synthesis workflows – as well as integration with purification and analysis – helping to ensure a constant and rapid supply of pure compounds ready for testing, while improving reproducibility and reducing costs compared with manual, serial compound synthesis (8, 9).
There are many benefits of flow chemistry in modern chemical synthesis, such as greater control of reaction parameters, improved selectivity, higher yields and increased reaction rates. Many of these benefits also apply specifically to drug discovery programs, including:
- Access to challenging or restrictive chemistries limited by traditional batch techniques
- Improved safety profiles, as reactive intermediates and hazardous reagents are created in situ
- Easy access to scale-up following small scale optimisation
- Efficient serial library generation, with the rapid exploration of diverse chemical spaces
- Ability to perform multi-step chemistries using a modular approach, allowing direct synthesis of complex compounds
- Easier access to reagentless chemistries, such as continuous electro- or photochemistry
- Greener and more efficient processes, saving money and the environment
Conclusion
The early drug discovery process has undergone a series of continuous improvements over the past two decades. The increased demand on all disciplines, especially chemists, has driven the implementation of new enabling technologies to reduce the time and costs involved in bringing novel drugs to market. Flow chemistry has made an impact in most areas of drug discovery and development, as well as in delivery and production. The development of automated techniques and the integration of synthesis with purification and analysis has greatly increased the speed with which novel compounds can be delivered, helping reduce the cycle times and accelerate the early stages of drug discovery.
Figure 1. Typical pharmaceutical product development timeline and number of compounds needed in the different phases to obtain one FDA-approved drug.
Figure 2. Iterative learning cycles of medicinal chemistry based on diverse discipline activities with examples of key approaches used today . Adapted from reference (3).
References and notes
- Novartis. Discovery The art of drug design in a technological age https://www.novartis.com/stories/art-drug-design-technological-age (accessed Mar 14, 2022).
- Cerra B et al. Exploiting Chemical Toolboxes for the Expedited Generation of Tetracyclic Quinolines as a Novel Class of PXR Agonists. ACS Med. Chem. Lett. 2019;10(4):677–681.
- Gioiello A, Piccinno A, Lozza AM, Cerra B. The Medicinal Chemistry in the Era of Machines and Automation: Recent Advances in Continuous Flow Technology. J. Med. Chem. 2020;63(13):6624–6647.
- López E, Alcazar J. Flow Chemistry in Drug Discovery: Challenges and Opportunities. In Flow Chemistry in Drug Discovery; Springer International Publishing: Berlin, Heidelberg, 2021;1–22.
- Lombardino JG, Loew JA. The role of the medicinal chemistry in drug discovery – then and now. Nat. Rev. Drug Discovery, 2004;3:853–862.
- Gomollón-Bel F. Ten Chemical Innovations That Will Change Our World: IUPAC Identifies Emerging Technologies in Chemistry with Potential to Make Our Planet More Sustainable. Chem. Int. 2019;41(2):12–17.
- Gottlieb S, Woodcock J. FDA statement on FDA’s modern approach to advanced pharmaceutical manufacturing. https://www.fda.gov/news-events/press-announcements/fda-statement-fdas-modern-approach-advanced-pharmaceutical-manufacturing (accessed Mar 15, 2022).
- Schneider G. Automating drug discovery. Nat. Rev. Drug Discovery, 2018;17:97–113
- Trobe M, Burke M D. The molecular industrial revolution: automating synthesis of small molecules. Angew. Chem., Int. Ed. 2018;57:4192–4214.
