Medicinal Chemistry

Medicinal chemistry is a multidisciplinary field at the intersection of chemistry, biology and pharmacology focused on the design, development, and optimization of biologically active compounds for therapeutic use. In the early stages of drug discovery, the focus is on the identification and synthesis of new chemical entities that can interact with specific biological targets. During the hit-to-lead optimization stage, the chemical structure of promising candidates is modified to enhance pharmacological properties, such as potency, selectivity, permeability, metabolic stability and solubility.

Navigating the Chemical Space

The challenge of exploring chemical space extends beyond its sheer size. Not all theoretically possible molecules can be synthesized easily, if at all. For those that can be synthesized, some may be highly unstable or reactive, making them difficult to isolate or study. AI and machine learning (ML) can help with navigating chemical space but the models they generate might be difficult to interpret.

To overcome these challenges, there is a growing need to combine AI/ML models with high throughput experimentation (HTE) to efficiently identify and validate novel compounds. In this hybrid approach, virtual screening is used to prioritize promising candidates, which are then experimentally validated through HTE. The data generated from HTE can be fed back into the virtual screening models, refining their predictions and real-world relevance in an iterative cycle. This process not only enhances the accuracy of models but also focuses exploration on the most promising regions of chemical space. Additionally, it enables rapid optimization of reaction conditions, significantly reducing the time and cost associated with the identification of novel drug candidates.

Since the curation of AI/ML models heavily depends on large volumes of high-quality experimental results, ensuring the accuracy of this data is paramount. Automating HTE has become critical to preventing the introduction of noise, false positives, and false negatives.

Advancing Chemistry with High-Throughput Techniques

In recent years, ultra-high throughput experimentation (uHTE) has emerged as a transformative approach. It significantly increases the number of data points generated per experiment, while simultaneously addressing the challenges associated with limited quantities of newly synthesized or rare compounds and the scarcity of substrates. Automated uHTE enables the simultaneous execution of over 1500 experiments at the nanomolar scale, significantly reducing material consumption and set-up time. This methodology accelerates the design-make-test learning cycle, enhancing efficiency in chemical exploration and compound optimization. Additionally, the reaction miniaturization supports sustainable practices by decreasing the volume of hazardous chemicals required and minimizing waste generation.

Enhancing Reproducibility

Ensuring consistency in HTE and uHTE experiments can be difficult due to the scale and speed of the process. Small variations in experimental conditions or human errors can lead to significant discrepancies in the results. These experiments often require precise pipetting of challenging solutions, such as metal catalysts or organic solvents, which are difficult to handle manually, especially when low volume transfers are needed. Advances in liquid handling technologies are addressing these issues effectively. mosquito LV, a low volume pipettor that is agnostic to liquid viscosity, enables the automated execution of multi-parallel synthesis at the nanomolar scale, facilitating precise and highly reproducible investigations of reaction discovery and optimization. These reactions include Suzuki cross-couplings, reductive aminations, N-alkylations, nucleophilic aromatic substitutions (S_NAr), as well as transition-metal catalyzed couplings such as the Pd-catalyzed Buchwald-Hartwig amination, metallophotoredox C–N and C–O bond formations, and C–H functionalizations (ref 1-7)

Evaporex® (EVX) evaporators seamlessly integrate into medicinal chemistry workflows, offering efficient solvent removal under controlled conditions, reducing well-to-well and plate-to-plate variability, and sample contamination risk. The instrument's high-throughput capabilities empower researchers to conduct large-scale screening experiments efficiently, accelerating the pace of drug discovery and development.

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