Early Drug Discovery Research Articles

Docking covalent targets for drug discovery: stimulating the computer-aided drug design community of possible pitfalls and erroneous practices.

The continuous approval of covalent drugs in recent years for the treatment of diseases has led to an increased search for covalent agents by medicinal chemists and computational scientists worldwide. In the computational parlance, molecular docking which is a popular tool to investigate the interaction of a ligand and a protein target, does not account for the formation of covalent bond, and the increasing application of these conventional programs to covalent targets in early drug discovery practice is a matter of utmost concern. Thus, in this comprehensive review, we sought to educate the docking community about the realization of covalent docking and the existence of suitable programs to make their future virtual-screening events on covalent targets worthwhile and scientifically rational. More interestingly, we went beyond the classical description of the functionality of covalent-docking programs down to selecting the ‘best’ program to consult with during a virtual-screening campaign based on receptor class and covalent warhead chemistry. In addition, we made a highlight on how covalent docking could be achieved using random conventional docking software. And lastly, we raised an alert on the growing erroneous molecular docking practices with covalent targets. Our aim is to guide scientists in the rational docking pursuit when dealing with covalent targets, as this will reduce false-positive results and also increase the reliability of their work for translational research.Graphical abstract

Metabolic clearance of select opioids and opioid antagonists using hepatic spheroids and recombinant cytochrome P450 enzymes.

The opioid crisis is a pressing public health issue, exacerbated by the emergence of more potent synthetic opioids, particularly fentanyl and its analogs. While competitive antagonists exist, their efficacy against synthetic opioids is largely unknown. Furthermore, due to the short durations of action of current antagonists, renarcotization remains a concern. In this study, metabolic activity was characterized for fentanyl‐class opioids and common opioid antagonists using multiple in vitro systems, namely, cytochrome P450 (CYP) enzymes and hepatic spheroids, after which an in vitro‐in vivo correlation was applied to convert in vitro metabolic activity to predictive in vivo intrinsic clearance. For all substrates, intrinsic hepatic metabolism was higher than the composite of CYP activities, due to fundamental differences between whole cells and single enzymatic reactions. Of the CYP isozymes investigated, 3A4 yielded the highest absolute and relative metabolism across all substrates, with largely negligible contributions from 2D6 and 2C19. Comparative analysis highlighted elevated lipophilicity and diminished CYP3A4 activity as potential considerations for the development of more efficacious opioid antagonists. Finally, antagonists with a high degree of molecular similarity exhibited comparable clearance, providing a basis for structure‐metabolism relationships. Together, these results provide multiple screening criteria for early stage drug discovery involving opioid countermeasures.

A Review of Computational Methods in Predicting hERG Channel Blockers

AbstractInhibition of the human ether‐à‐go‐go‐related gene (hERG) ion channel may lead to prolonged QT interval and even fatal ventricular arrhythmia. Therefore, evaluating the hERG liability has become a mandatory requirement for drug development and drug safety process. However, standard experimental assays are complex, expensive and time‐consuming. Various in silico tools have been developed to identify potential hERG blockers and reduce in advance the risk of cardiotoxicity‐related attritions during the early drug discovery phase. In this review, we first outlined the structure and gating properties of the hERG channel briefly. Then analyzed the advantages of computational technology, and comprehensively summarized the in silico methods of hERG‐related cardiotoxicity, including ligand‐based and structure‐based methods. Additionally, the current predictive models in prediction of hERG blockage were emphatically reviewed. Finally, issues involved in the current computational methods, as well as the future direction for developing reliable models of hERG channel blockers, are discussed.

Time matters – in vitro cellular disposition kinetics help rationalizing cellular potency disconnects

Loss in potency is commonly observed in early drug discovery when moving from biochemical to more complex cellular systems. Among other factors, low permeability is often considered to cause such potency disconnects. We developed a novel cellular disposition assay in MDCK cells to determine passive uptake clearance (PSinf), cell-to-medium ratios at steady-state (K p) and the time to reach 90% steady-state (TTSS90) from a single experiment in a high-throughput format. The assay was validated using 40 marketed drugs, showing a wide distribution of PSinf and K p values. The parameters generally correlated with transcellular permeability and lipophilicity, while PSinf data revealed better resolution in the high and low permeability ranges compared to traditional permeability data. A linear relationship between the K p/PSinf ratio and TTSS90 was mathematically derived and experimentally validated, demonstrating the dependency of TTSS90 on the rate and extent of cellular accumulation. Cellular disposition parameters could explain potency (IC50) disconnects noted for seven Bruton’s tyrosine kinase degrader compounds in a cellular potency assay. In contrast to transcellular permeability, PSinf data enabled identification of the compounds with IC50 disconnects based on their time to reach equilibrium. Overall, the novel assay offers the possibility to address potency disconnects in early drug discovery.

Virtual Screening in the Cloud Identifies Potent and Selective ROS1 Kinase Inhibitors.

ROS1 rearrangements account for 1-2% of non-small cell lung cancer patients, yet there are no specifically designed, selective ROS1 therapies in the clinic. Previous knowledge of potent ROS1 inhibitors with selectivity over TrkA, a selected antitarget, enabled virtual screening as a hit finding approach in this project. The ligand-based virtual screening was focused on identifying molecules with a similar 3D shape and pharmacophore to the known actives. To that end, we turned to the AstraZeneca virtual library, estimated to cover 1015 synthesizable make-on-demand molecules. We used cloud computing-enabled FastROCS technology to search the enumerated 1010 subset of the full virtual space. A small number of specific libraries were prioritized based on the compound properties and a medicinal chemistry assessment and further enumerated with available building blocks. Following the docking evaluation to the ROS1 structure, the most promising hits were synthesized and tested, resulting in the identification of several potent and selective series. The best among them gave a nanomolar ROS1 inhibitor with over 1000-fold selectivity over TrkA and, from the preliminary established SAR, these have the potential to be further optimized. Our prospective study describes how conceptually simple shape-matching approaches can identify potent and selective compounds by searching ultralarge virtual libraries, demonstrating the applicability of such workflows and their importance in early drug discovery.

A discovery biotransformation strategy: combining in silico tools with high-resolution mass spectrometry and software-assisted data analysis for high-throughput metabolism

Understanding compound metabolism in early drug discovery aids medicinal chemistry in designing molecules with improved safety and ADME properties. While advancements in metabolite prediction brings increased confidence, structural decisions require experimental data. In vitro metabolism studies using liquid chromatography and high-resolution mass spectrometry (LC–MS) are generally resource intensive and performed on very few compounds, limiting the chemical space that can be examined. Here, we describe a novel metabolism strategy increasing compound throughput using residual in vitro clearance samples conducted at drug concentrations of 0.5 µM. Analysis by robust ultra high-performance liquid chromatography separation and accurate-mass MS detection ensures major metabolites are identified from a single injection. In silico prediction (parent cLogD) tailors chromatographic conditions, with data-dependent tandem mass spectroscopy targeting predicted metabolites. Software-assisted data mining, structure elucidation and automatic reporting are used. Confidence in the globally aligned workflow is demonstrated with 16 marketed drugs. The approach is now implemented routinely across our laboratories. To date, the success rate for identification of at least one major metabolite is 85%. The utility of these data has been demonstrated across multiple projects, allowing earlier medicinal chemistry decisions to increase efficiency and impact of the design–make–test cycle thus improving the translatability of early in vitro metabolism data.

Small Molecular Drug Screening Based on Clinical Therapeutic Effect

Virtual screening can significantly save experimental time and costs for early drug discovery. Drug multi-classification can speed up virtual screening and quickly predict the most likely class for a drug. In this study, 1019 drug molecules with actual therapeutic effects are collected from multiple databases and documents, and molecular sets are grouped according to therapeutic effect and mechanism of action. Molecular descriptors and molecular fingerprints are obtained through SMILES to quantify molecular structures. After using the Kennard–Stone method to divide the data set, a better combination can be obtained by comparing the combined results of five classification algorithms and a fusion method. Furthermore, for a specific data set, the model with the best performance is used to predict the validation data set. The test set shows that prediction accuracy can reach 0.862 and kappa coefficient can reach 0.808. The highest classification accuracy of the validation set is 0.873. The more reliable molecular set has been found, which could be used to predict potential attributes of unknown drug compounds and even to discover new use for old drugs. We hope this research can provide a reference for virtual screening of multiple classes of drugs at the same time in the future.

Accelerating the Validation of Endogenous On-Target Engagement and In Cellulo Kinetic Assessment for Covalent Inhibitors of KRASG12C in Early Drug Discovery.

Covalent inhibition is a valuable modality in drug discovery because of its potential ability in decoupling pharmacokinetics from pharmacodynamics by prolonging the residence time of the drug on the target of interest. This increase in target occupancy is limited only by the rate of target turnover. However, a limitation in such studies is to translate the in vitro inhibition assessment to the appropriate in cellulo target engagement parameter by covalent probes. Estimation of such parameters is often impeded by the low-throughput nature of current probe-free approaches. In this study, an ultra-performance liquid chromatography-multiple reaction monitoring mass spectrometry platform was utilized to develop a targeted proteomics workflow that can evaluate cellular on-target engagement of covalent molecules in an increased throughput manner. This workflow enabled a throughput increase of 5-10 fold when compared to traditional nanoLC-based proteomics studies. To demonstrate the applicability of the method, KRASG12C was used as a model system to investigate the interaction of an irreversible covalent small molecule, compound 25, both in vitro and in cellulo. Initial biochemical studies confirmed that the small molecule forms an adduct with the targeted cysteine on the protein, as assessed at the level of both intact protein and on the target peptide. In cellulo studies were carried out to quantify target engagement and allele selectivity assessment for the small molecule in the heterozygous NCI-H358 cell line for KRASG12C with respect to the WT type protein. The workflow enabled evaluation of in vitro and in cellulo target engagement kinetics, providing mechanistic insights into the irreversible mode of inhibition. In summary, the method has the potential for target agnostic application in the assessment of on-target engagement of covalent probes compatible with the high-throughput requirements of early drug discovery.

18O-Enabled High-Throughput Acyl Glucuronide Stability Assay.

Acyl glucuronides (AGs) are common metabolites of carboxylic acid-containing compounds. In some circumstances, AGs are suspected to be involved in drug toxicity due to formation of acyl migration products that bind covalently to cellular components. The risk of this adverse effect has been found to be correlated with the chemical stability of the AG, and assays have been described that monitor acyl migration by liquid chromatography coupled with mass spectrometry (LC-MS). This analysis can be challenging as it requires baseline chromatographic separation of the unmigrated 1-β-acyl glucuronide from the migrated isomers and thus needs to be individually optimized for each aglycone. Therefore, a high-throughput assay that eliminates LC method development is desirable. Herein, we report an improved acyl glucuronide stability assay based on the rate of 18O-incorporation from [18O] water, which is compatible with high-throughput bioanalytical LC-MS workflows. Synthetic AGs with shorter migration half-lives showed faster incorporation of 18O. The level of differential incorporation of 18O following a 24 h incubation correlates well with the migration tendency of AGs. This assay was developed further, exploring in situ generation of AGs by human hepatic microsomal fraction. The results from 18 in situ-formed acyl glucuronides were similar to those obtained using authentic reference standards. In this format, this new 18O-labeling method offers a simplified workflow, requires no LC method development or AG reference standard, and thus facilitates AG liability assessment in early drug discovery.

Mass Spectrometry Detection and Imaging of a Non-Covalent Protein-Drug Complex in Tissue from Orally Dosed Rats.

Here, we demonstrate detection by mass spectrometry of an intact protein–drug complex directly from liver tissue from rats that had been orally dosed with the drug. The protein–drug complex comprised fatty acid binding protein 1, FABP1, non‐covalently bound to the small molecule therapeutic bezafibrate. Moreover, we demonstrate spatial mapping of the [FABP1+bezafibrate] complex across a thin section of liver by targeted mass spectrometry imaging. This work is the first demonstration of in situ mass spectrometry analysis of a non‐covalent protein–drug complex formed in vivo and has implications for early stage drug discovery by providing a route to target‐drug characterization directly from the physiological environment.

Mass Spectrometry Detection and Imaging of a Non-Covalent Protein-Drug Complex in Tissue from Orally Dosed Rats.

Here, we demonstrate detection by mass spectrometry of an intact protein-drug complex directly from liver tissue from rats that had been orally dosed with the drug. The protein-drug complex comprised fatty acid binding protein 1, FABP1, non-covalently bound to the small molecule therapeutic bezafibrate. Moreover, we demonstrate spatial mapping of the [FABP1+bezafibrate] complex across a thin section of liver by targeted mass spectrometry imaging. This work is the first demonstration of in situ mass spectrometry analysis of a non-covalent protein-drug complex formed in vivo and has implications for early stage drug discovery by providing a route to target-drug characterization directly from the physiological environment.

Blood–brain barrier penetration prediction enhanced by uncertainty estimation

Blood–brain barrier is a pivotal factor to be considered in the process of central nervous system (CNS) drug development, and it is of great significance to rapidly explore the blood–brain barrier permeability (BBBp) of compounds in silico in early drug discovery process. Here, we focus on whether and how uncertainty estimation methods improve in silico BBBp models. We briefly surveyed the current state of in silico BBBp prediction and uncertainty estimation methods of deep learning models, and curated an independent dataset to determine the reliability of the state-of-the-art algorithms. The results exhibit that, despite the comparable performance on BBBp prediction between graph neural networks-based deep learning models and conventional physicochemical-based machine learning models, the GROVER-BBBp model shows greatly improvement when using uncertainty estimations. In particular, the strategy combined Entropy and MC-dropout can increase the accuracy of distinguishing BBB + from BBB − to above 99% by extracting predictions with high confidence level (uncertainty score < 0.1). Case studies on preclinical/clinical drugs for Alzheimer’ s disease and marketed antitumor drugs that verified by literature proved the application value of uncertainty estimation enhanced BBBp prediction model, that may facilitate the drug discovery in the field of CNS diseases and metastatic brain tumors.

NTD Drug Discovery Booster, Achievements and Next Steps

The Neglected Tropical Disease (NTD) Drug Discovery Booster is a collaborative project in early small molecule drug discovery running since 2015 between Drugs for Neglected Diseases initiative (DNDi) and pharmaceutical partners across the globe, including Astellas Pharma Ltd., Eisai Co., Ltd., Shionogi & Co., Ltd. and Takeda Pharmaceutical Company Ltd. in Japan, along with AbbVie Inc., Merck KGaA, AstraZeneca plc and Celgene Corporation. The Booster engages these partners to share both their experience with in silico screening as well as their proprietary chemical libraries to further develop new starting points for NTDs such as visceral leishmaniasis and Chagas disease. This collaborative approach allows DNDi to access new chemical space and elaborate the structure activity relationships (SAR) around phenotypic screening hits against the causative parasites of these diseases (Trypanosoma cruzi, Leishmania donovani and infantum) as well as access new starting points via innovative scaffold hops proposed by the partners. Since 2015 the Booster has probed over 20 new starting point "hits" for these diseases, successfully converting over half into new series for further exploitation. These series were developed further in partnership with the booster collaborators to enable in vivo proof of concept studies, with series from the booster progressing into lead optimization. Our efforts in the NTD Discovery Booster have demonstrated clear advantages of this precompetitive sharing mechanism and the synergistic value of exploring multiple proprietary compound libraries in parallel. The most advanced of these Booster projects is projected to deliver a preclinical candidate for leishmaniasis within the next 2 years.

A high-throughput screening assay for mutant isocitrate dehydrogenase 1 using acoustic droplet ejection mass spectrometry.

Acoustic droplet ejection mass spectrometry (ADE-MS) has recently emerged as a promising label-free, MS-based readout method for high throughput screening (HTS) campaigns in early pharmaceutical drug discovery, since it enables high-speed analysis directly from 384- or 1536-well plates. In this manuscript we describe our characterization of an ADE-MS based high sample content enzymatic assay for mutant isocitrate dehydrogenase 1 (IDH1) R132H with a strong focus on assay development. IDH1 R132H has become a very attractive therapeutic target in the field of antitumor drug discovery, and several pharmaceutical companies have attempted to develop novel small molecule inhibitors against mutant IDH1. With the development of an mIDH1 ADE-MS based HTS assay and a detailed comparison of this new readout technique to the commonly used fluorescence intensity mIDH1 assay, we demonstrated good correlation of both methods and were able to identify new potent inhibitors of mIDH1.

Feasibility of establishing a veterinary marker to total residue in edible tissues with non-radiolabeled study using high-resolution mass spectrometry

Traditionally, in vivo metabolism and total residue studies in veterinary drug research were conducted using radiolabeled drug where information on metabolite profiles and marker residue to total residue ratio is obtained. The Veterinary International Conference on Harmonisation (VICH) guideline GL46 indicates that the metabolism and residue kinetics in food-producing animals may be documented by an alternative approach, one other than the traditional radiolabeled study. High-resolution mass spectrometry (HRMS) has been widely used in human pharmaceutical R&D from metabolite profiling and identification in early drug discovery to first-in-human (FIH) studies in development. Recent advances in data mining tools have greatly improved the metabolite profiling capability with HRMS. It is now routine to study metabolism using non-radiolabeled samples without missing any major metabolites. In the current paper, we explored the feasibility of conducting non-radiolabeled marker residue studies to obtain metabolism information using HRMS. Metabolite profiles of gamithromycin in edible tissues of sheep treated with 6 mg/kg body weight subcutaneous injections were obtained with HRMS. The semi-quantitative relationship between the level of gamithromycin and the total treatment-related residues was established by determining the percentages of extracted ion chromatograms for metabolites and parent compound residues in each tissue. Major components (gamithromycin and its metabolite, declad) were measured quantitatively using a validated liquid chromatography/tandem mass spectrometry (LC-MS/MS) method. Metabolite profiles in excreta were also obtained and the major components measured quantitatively with a LC-MS/MS method to ensure no major metabolite was missing. Combining previous knowledge of marker residue studies in cattle and swine, as well as an in vitro comparative metabolism study with metabolite data across various species, gamithromycin was designated as the marker residue in sheep edible tissues. The marker to total residue ratios were established using a combination of the semi-quantitative HRMS results and quantitative results with the major components: the marker residue and declad. The pros and cons of the HRMS method as well as the appropriate use of the method for marker residue studies are discussed.

Abstract 1637: PDX-derived cell line platform for pharmacological screening and functional studies

Abstract Despite considerable progress in understanding the biology and genetics of cancer, the development of effective therapies is hampered by the lack of sufficient experimental models that recapitulate the genetic diversity of this disease. The recourse to patient-derived xenograft (PDX) for the evaluation of new candidate anticancer drugs is becoming the gold standard in preclinical oncology. The faithful reproduction of patients’ cancer features, and the possibility to generate a large number of models that recapitulate patient population genetic heterogeneity, confer PDXs a critical added value in the evaluation of new candidate drugs. These improved models will hopefully contribute to decrease the attrition rate observed in clinical trials, thus far unacceptably high. Over the last 15 years, we have generated and characterized a collection of 200+ PDXs from different solid tumors that accurately reproduce the histological and molecular heterogeneity of the tumors of origin. This panel has allowed for the preclinical validation of several anticancer drugs that are now used in the clinic. Although being an indispensable tool to complete preclinical studies, the use of PDX in vivo systems for large-scale screening during early drug discovery is hampered by ethical, economical and throughput burdens limiting the number of test articles being tested. To address this problem, we developed a panel of PDX-derived cell lines (PDXDCs) that we propose as a time and cost-effective medium-throughput screening tool to profile the anti-cancer activity of early test compounds. To date, 50+ PDXDCs from various indications such as breast, lung, prostate and many others have been generated and tested for their response in vitro towards standards of care and targeted anti-cancer agents matching patient clinical management. Differently from standard cell line establishment, which is obtained by expansion of a cell clone that survives in vitro plating, our cell line development technology allows for maintenance of tumor cell population heterogeneity. PDXDCs RNA and exome sequencing data faithfully match the parental PDX features, and by modulating experimental parameters, such as 2D or 3D growth conditions, drug exposure duration and endpoint read-outs, we could phenocopy in vitro the corresponding PDXs’ sensitivities to chemotherapies. These results show our PDXDCs panel is a valuable in vitro platform for drug screening to help selecting drug candidates for further validation in parental PDX models in vivo. Citation Format: Olivier Déas, Léa Sinayen, Emilie Indersie, Kathleen Flosseau, Sophie Banis, Enora Le Ven, Jean-Gabriel Judde, Stefano Cairo. PDX-derived cell line platform for pharmacological screening and functional studies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1637.

Abstract 1870: A simple and quantitative immunoassay for evaluation of receptor occupancy and antibody binding capacity in fixed cells or tissue samples for immune-directing antibody development

Abstract Receptor occupancy (RO) assays are used to quantify the binding of therapeutic antibodies to their targets on the cell surface. This method can be used to in early drug discovery to determine the antibody binding capacity (ABC) of drug candidates to cells in culture to hone the desired drug characteristics during candidate screening or lead optimization. This method can also be used in xenografts or patient tissues to create pharmacodynamic (PD) data that directs the efficacy hypothesis and biomarker selection for clinical trials. The current approaches use flow cytometry on fresh specimens, which introduces many technical and logistical challenges and does not retain spatial information about the tissue. Here we introduce a new, simple method which can be performed on Formalin Fixed, Paraffin Embedded (FFPE) cells or tissues. This approach eliminates the challenges of flow cytometry methods, provides the type of quantitative data needed, and maintains the tissue contexture to study the effects of immune-directing antibodies in patient tissue samples. We describe a method for developing a standard curve to determine antibody binding capacity (ABC) using our Quanticell ™ fluorescent nanoparticle technology. We demonstrate this in a typical bispecific antibody use case, where both the immune-directing (CD3) and targeting (Her2) arms of the bispecific are modulated to create the desired efficacy characteristics. We demonstrate the establishment of a standard calibration curve for Her2 (BT474/Her2+) and CD3 (Jurkat/CD3+) in cells with titrated amounts of anti-Her2 and anti-CD3 antibodies which target the extracellular domain necessary for these studies. We also show how the same Quanticell assay can be used in clinical tissue, to evaluate the localization of the drug targets and immune cells within the tissue context of human patient samples necessary to understand how pharmacodynamic properties of the drug can modulate immune contexture changes. The Quanticell™ method is a simple immunohistochemistry (IHC) based method which allows extremely sensitive detection of therapeutic antibodies bound on FFPE fixed cells or tissue, which thus does not require the use of flow cytometry in fresh tissues, allowing simple use from early discovery through clinical research studies. Importantly, the Quanticell™ method is capable of detecting a very large and linear dynamic range of analyte concentration to allow full quantification of ABC for RO studies. Critically, the Quanticell™ method retains the tissue context, allowing for simultaneous and spatial evaluation of multiple analytes such as the target of the antibody and the immune contexture. This method allows for a consistent method for RO studies that can be applied to early discovery, translational, and clinical research to optimize drug efficacy. Citation Format: Atsuro Tatsumi, Keisuke Morichika, Caroline Morel, Omid Ghasemi, Hiroyuki Yokota, Joseph S. Krueger. A simple and quantitative immunoassay for evaluation of receptor occupancy and antibody binding capacity in fixed cells or tissue samples for immune-directing antibody development [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1870.

Abstract 2323: A bioenergetic functional screening assay workflow to identify, validate, and characterize anti-cancer compounds

Abstract As bioenergetic metabolism is recognized as a critical activity supporting cell proliferation, differentiation, and even death, many proposed targets for cancer therapy are functionally linked to cellular bioenergetic metabolism. Here, we introduce an assay workflow for screening and analyzing potential anticancer drugs affecting cellular metabolism using extracellular flux analysis. The Agilent Seahorse XF Real-Time ATP rate assay can be used as a starting point to identify therapeutic compounds that induce a perturbation in metabolic phenotype. It provides a quantitative comparison of basal mitochondrial and glycolytic activities using the universal unit of ATP production rate. Through this initial comparative screening, the effect of different compounds on basal energetic state and pathway-specific metabolic perturbations can be identified providing information that cannot be assessed by intracellular ATP level measurements or cytotoxicity assays. A more comprehensive functional analysis can then be applied to validate the target mode of action through pathway-specific analysis tools such as the XF Cell Mito Stress Test and the XF Glycolytic Rate Assay. In this study, we tested the proposed workflow in three different NSCLC cell lines with different genetic backgrounds using a mock panel of known metabolic modulators including thiosemicarbazones, EGFR inhibitors, KRAS inhibitors, a glutaminase inhibitor, a Glut1 inhibitor, a chemotherapy drug, and a radiotherapy sensitizer candidate. The ATP production rate data from lung cancer cell lines exposed for 1 hour or 24 hours to the compounds, successfully identified the effects of metabolic pathway-specific modulation as well as metabolic phenotypic switching. In addition, dose-response studies using cell lines with different genetic backgrounds demonstrated differential susceptibility to the tested compounds. The workflow was then applied using a broader panel of 72 potential mitochondrial toxicants compounds. The assay could identify potent mitochondrial and glycolytic suppressor compounds effective on A549, a lung cancer cell line. A more comprehensive XF analysis then validated the mode of action for the identified metabolic suppressors. These results demonstrate the benefit of using the XF Real-Time ATP rate assay as an initial assay to uncover novel metabolic targets in early drug discovery research, guiding further research toward functional validation with the appropriate comprehensive XF assays. Citation Format: Yoonseok Kam, Lisa Winer, Natalia Romero. A bioenergetic functional screening assay workflow to identify, validate, and characterize anti-cancer compounds [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2323.

Abstract 605: MoA-based potency bioassays for immunotherapy programs targeting the TIGIT/CD112R/CD226 axis

Abstract Immune checkpoint (IC) receptors play critical roles in maintaining immune homeostasis and have emerged as proven drug targets for the treatment of various cancers and autoimmune disorders. Monoclonal antibodies (mAb) designed to block immune inhibitory receptors PD-1 and CTLA-4 have been approved and show unprecedented efficacy in cancer treatment. This led to rapid expansion of drug development to many more IC receptors including members of the T cell immunoreceptor with Ig and ITIM domains (TIGIT) - CD112R (PVRIG) - CD226 Axis. TIGIT binds to its ligands CD155 (PVR) and CD112 (PVRL2) while CD112R binds to CD112. Binding of TIGIT or CD112R to CD155/CD112 inhibits the co-stimulatory activity of the paired receptor CD226. Thus, therapeutic targeting of this axis can modulate T cell and NK cell activation and unleash anti-cancer immunity. One of the bottlenecks of immunotherapy drug development is the lack of quantitative and reproducible functional assays for mAb potency determination. Existing methods rely heavily on primary immune cells which is labor intensive and highly variable. To address this need, we developed a panel of cell-based reporter bioassays that can quantitatively measure the potencies of mAbs targeting TIGIT/CD155, TIGIT/CD112, and CD112R/CD112. Owing to positive clinical trial results of TIGIT blockade in combination with PD-1/PD-L1 blockade, we further developed a potency bioassay for bispecific antibodies simultaneously targeting TIGIT and PD-1/PD-L1. These bioassays each consist of an engineered T effector cell line that expresses T cell receptors and IC receptors of interest, and an engineered artificial antigen presenting cells (aAPC) expressing the corresponding ligands for the IC receptors. The T effector cell lines also express a luciferase reporter driven by a promoter specifically responding to TCR activation which can be inhibited by signaling from the IC receptors. Additionally, we developed bioassays that can measure potencies of agonist or antagonist mAbs targeting CD226. These bioassays are designed to reflect the mechanisms of action for the drug candidates designed for each IC receptor and the assay signals are specific. Most are prequalified according to ICH guidelines and show the precision, accuracy and linearity required for relative potency determination and product stability study under cGMP environments. Therefore, these MoA-based bioassays can serve as valuable tools for early drug discovery, potency determination and stability studies throughout the development of mAbs targeting the TIGIT/CD112R/CD226 axis. Citation Format: Jamison Grailer, Denise Garvin, Jim Hartnett, Frank Fan, Mei Cong, Zhi-Jie Jey Cheng. MoA-based potency bioassays for immunotherapy programs targeting the TIGIT/CD112R/CD226 axis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 605.

Early Feasibility Assessment: A Method for Accurately Predicting Biotherapeutic Dosing to Inform Early Drug Discovery Decisions.

The application of model-informed drug discovery and development (MID3) approaches in the early stages of drug discovery can help determine feasibility of drugging a target, prioritize between targets, or define optimal drug properties for a target product profile (TPP). However, applying MID3 in early discovery can be challenging due to the lack of pharmacokinetic (PK) and pharmacodynamic (PD) data at this stage. Early Feasibility Assessment (EFA) is the application of mechanistic PKPD models, built from first principles, and parameterized by data that is readily available early in drug discovery to make effective dose predictions. This manuscript demonstrates the ability of EFA to make accurate predictions of clinical effective doses for nine approved biotherapeutics and outlines the potential of extending this approach to novel therapeutics to impact early drug discovery decisions.