Automated Supersaturation Stability Assay to Differentiate Poorly Soluble Compounds in Drug Discovery

Free Energy Perturbation Approach for Accurate Crystalline Aqueous Solubility Predictions

Early assessment of crystalline thermodynamic solubility continues to be elusive for drug discovery and development despite its critical importance, especially for the ever-increasing fraction of poorly soluble drug candidates. Here we present a detailed evaluation of a physics-based free energy perturbation (FEP+) approach for computing the thermodynamic aqueous solubility. The predictive power of this approach is assessed across diverse chemical spaces, spanning pharmaceutically relevant literature compounds and more complex AbbVie compounds. Our approach achieves predictive (RMSE = 0.86) and differentiating power (R2 = 0.69) and therefore provides notably improved correlations to experimental solubility compared to state-of-the-art machine learning approaches that utilize quantum mechanics-based descriptors. The importance of explicit considerations of crystalline packing in predicting solubility by the FEP+ approach is also highlighted in this study. Finally, we show how computed energetics, including hydration and sublimation free energies, can provide further insights into molecule design to feed the medicinal chemistry DMTA cycle.

High-throughput kinetic turbidity analysis for determination of amorphous solubility and excipient screening for amorphous solid dispersions

Many poorly water-soluble active pharmaceutical ingredients (APIs) rely on supersaturating formulations, such as amorphous solid dispersions (ASDs), to enhance oral bioavailability. ASDs kinetically trap amorphous solid drugs within polymer excipient matrices to maintain the amorphous drug states. The maximum solution concentration of the API in these formulations is known as the amorphous solubility. In early drug development with scarce material and time, high-throughput approaches to measuring amorphous solubility and screening excipient effects on crystallization risk offer significant benefits to preclinical formulation scientists. Here, we developed a high-throughput screening (HTS) workflow to quantify amorphous solubility and screen ASD excipients by automated kinetic turbidity analysis. Testing 20 model APIs with a wide range of biorelevant solubility, we demonstrated their apparent amorphous solubility determined by the HTS approach strongly correlated with quantification results using conventional liquid chromatography; while the real-time analysis significantly saved analytical time and experimental efforts. Furthermore, kinetic turbidity profiles elucidated distinct excipient effects on the precipitation process of APIs. These results were successfully translated to dissolution and precipitation behaviors of ASD formulations composed of the tested polymers. The high-throughput kinetic turbidity workflow presents a facile and information-rich approach for amorphous solubility screenings against excipients, and helps guide enabling formulation development.

Discovery solubility measurement and assessment of small molecules with drug development in mind

Solubility is a key physicochemical property for the success of any drug candidate. Although the methods used and their rationales for determining solubility are subject to project needs and stages along the drug discovery-drug development pipeline, an artificial boundary can exist at the discovery-development interface. This boundary results in less effective solubility knowledge sharing and data integration among scientists in both drug discovery and drug development. Herein, we present a refreshed perspective on solubility. Solubility experimentation is not a one-size-fits-all measurement; instead, we stress the importance of constructing a seamless solubility understanding of a molecule as it progresses from a new chemical entity into a drug product.

Prediction of in vivo supersaturation and precipitation of poorly water-soluble drugs: Achievements and aspirations

This review focuses on options available to a pharmaceutical scientist to predict in vivo supersaturation and precipitation of poorly water-soluble drugs. As no single device or system can simulate the complex gastrointestinal environment, a combination of appropriate in vitro tools may be utilized to get optimal predictive information. To address the empirical issues encountered during small-scale and full-scale in vitro predictive testing, theoretical background and relevant case studies are discussed. The practical considerations for selection of appropriate tools at various stages of drug development are recommended. Upcoming technologies that have potential to further reduce in vivo studies and expedite the drug development process are also discussed.

Discovery and Characterization of Clinical Candidate LXE408 as a Kinetoplastid-Selective Proteasome Inhibitor for the Treatment of Leishmaniases

Visceral leishmaniasis is responsible for up to 30,000 deaths every year. Current treatments have shortcomings that include toxicity and variable efficacy across endemic regions. Previously, we reported the discovery of GNF6702, a selective inhibitor of the kinetoplastid proteasome, which cleared parasites in murine models of leishmaniasis, Chagas disease, and human African trypanosomiasis. Here, we describe the discovery and characterization of LXE408, a structurally related kinetoplastid-selective proteasome inhibitor currently in Phase 1 human clinical trials. Furthermore, we present high-resolution cryo-EM structures of the Leishmania tarentolae proteasome in complex with LXE408, which provides a compelling explanation for the noncompetitive mode of binding of this novel class of inhibitors of the kinetoplastid proteasome.

Preformulation Studies and Enabling Formulation Selection for an Insoluble Compound at Preclinical Stage-From In Vitro, In Silico to In Vivo

The objective of this work was to identify an enabling formulation for an insoluble compound ZL006 with potency of boosting leukocytes after chemotherapy. The low oral bioavailability (<1%) of its conventional suspension was the hurdle for the preclinical evaluation via oral administration. Preformulation studies including physical form screening and physicochemical properties determination were performed. Polymorphism was observed, and the more thermodynamically stable form was selected for further studies. ZL006 showed certain supersaturation solubility, although the thermodynamic solubility in FaSSIF was low, which indicated the supersaturating formulation might work. Parameter sensitivity analysis by in silico simulation predicted that in vivo exposure was sensitive to solubility, while particle size reduction would have limited impact on exposure. Based on in silico prediction and the understanding of the molecule from preformulation studies, solid dispersion approach was selected. A preliminary dose escalation pharmacokinetic study in rats demonstrated that in vivo exposure increased in dose-proportional manner from 12.5 mg/kg to 50 mg/kg with around 50% oral bioavailability after oral dosing of the solid dispersion. This work showed that combination of preformulation studies and in silico simulation could efficiently guide the selection of enabling formulation, which could save resources at preclinical stage.

Brief overview of solubility methods: Recent trends in equilibrium solubility measurement and predictive models

Solubility is a crucial physicochemical parameter affecting the whole process of drug discovery and development. Thus, understanding of the methods and concepts to measure and predict this propensity are of utmost importance for the pharmaceutical scientist. Despite their inherent limitations, kinetic solubility screening methods became routine assays by mimicking bioassay conditions and guiding the lead optimization process. In contrast, thermodynamic solubility methods show a clear evolution: miniaturized high throughput assays coupled to analytical techniques such as solid-state characterization, ultra performance liquid chromatography, or polychromatic turbidimetry, have been developed, thereby enabling a more complex physicochemical profiling at the early discovery stage. Solubility prediction still poses a significant challenge at the industrial level. Classification and critical evaluation of recent in silico models are provided. Discussion of experimental and computational methods: was based on relevant industrial references.

Automated assays for thermodynamic (equilibrium) solubility determination

Solubility is a crucial physicochemical property for drug candidates and is important in both drug discovery and development. Poor solubility is detrimental to absorption after oral administration and can mask compound activity in bioassays in various ways. Hence, solubility liabilities should ideally be identified as early as possible in the drug development process. With the increasing number of compounds as potential drug candidates, automated thermodynamic solubility assays for high throughput screening enabling rapid evaluation of a large number of compounds are becoming increasingly important. This review discusses the current status of the most widely used automated assays for thermodynamic solubility, followed by recent high throughput measurements of properties related to solubility (e.g. dissolution rate and supersaturation) and a brief overview of predictive computational methods for thermodynamic solubility reported in the literature.