Evaluation of BH3 mimetics as a combination therapy with irradiation in head and neck squamous cell carcinoma.

INTRODUCTION: Head and neck squamous cell carcinoma (HNSCC) is a common cancer with a five-year survival rate around 60%, indicating a need for new treatments. BH3 mimetics are small molecules that inhibit anti-apoptotic Bcl-2 family proteins, resulting in apoptosis induction. METHODS: We performed a high-throughput screen using a Myogel matrix to identify the synergy between irradiation and the novel BH3 mimetics A-1155463, A-1331852, and navitoclax in 12 HNSCC cell lines, normal (NOF) and cancer-associated fibroblasts (CAF), and dysplastic keratinocytes (ODA). Next, we examined synergy in an apoptosis assay, followed by a clonogenic assay and a Myogel spheroid on selected HNSCC cell lines. Finally, we applied zebrafish larvae xenograft to validate the effects of navitoclax and A-1331852. RESULTS: All three BH3 mimetics exhibited a strong synergy with irradiation in eight HNSCC cell lines and ODAs, but not in NOFs and CAFs. A-1155463 and A-1331852 induced apoptosis and reduced proliferation, and together with irradiation, significantly increased apoptosis and arrested proliferation. A-1331852 and navitoclax significantly decreased the clonogenicity compared with the control, and combination treatment led to a decreased clonogenicity compared with monotherapy or irradiation. However, unlike navitoclax or A-1155463, only A-1331852 significantly reduced cancer cell invasion. Furthermore, in spheroid and zebrafish, irradiation appeared ineffective and failed to significantly increase the drug effect. In the zebrafish, A-1331852 and navitoclax significantly reduced the tumor area and metastasis. CONCLUSIONS: Our findings encourage the further preclinical investigation of BH3 mimetics, particularly A-1331852, as a single agent or combined with irradiation as a treatment for HNSCC.

Drug repurposing platform for deciphering the druggable SARS-CoV-2 interactome.

The coronavirus disease 2019 (COVID-19) pandemic has heavily challenged the global healthcare system. Despite the vaccination programs, the new virus variants are circulating. Further research is required for understanding of the biology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and for discovery of therapeutic agents against the virus. Here, we took advantage of drug repurposing to identify if existing drugs could inhibit SARS-CoV-2 infection. We established an open high throughput platform for in vitro screening of drugs against SARS-CoV-2 infection. We screened ∼1000 drugs for their ability to inhibit SARS-CoV-2-induced cell death in the African green monkey kidney cell line (Vero-E6), analyzed how the hit compounds affect the viral N (nucleocapsid) protein expression in human cell lines using high-content microscopic imaging and analysis, determined the hit drug targets in silico, and assessed their ability to cause phospholipidosis, which can interfere with the viral replication. Duvelisib was found by in silico interaction assay as a potential drug targeting virus-host protein interactions. The predicted interaction between PARP1 and S protein, affected by Duvelisib, was further validated by immunoprecipitation. Our results represent a rapidly applicable platform for drug repurposing and evaluation of the new emerging viruses' responses to the drugs. Further in silico studies help us to discover the druggable host pathways involved in the infectious cycle of SARS-CoV-2.

Image-based and machine learning-guided multiplexed serology test for SARS-CoV-2.

We present a miniaturized immunofluorescence assay (mini-IFA) for measuring antibody response in patient blood samples. The method utilizes machine learning-guided image analysis and enables simultaneous measurement of immunoglobulin M (IgM), IgA, and IgG responses against different viral antigens in an automated and high-throughput manner. The assay relies on antigens expressed through transfection, enabling use at a low biosafety level and fast adaptation to emerging pathogens. Using severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as the model pathogen, we demonstrate that this method allows differentiation between vaccine-induced and infection-induced antibody responses. Additionally, we established a dedicated web page for quantitative visualization of sample-specific results and their distribution, comparing them with controls and other samples. Our results provide a proof of concept for the approach, demonstrating fast and accurate measurement of antibody responses in a research setup with prospects for clinical diagnostics.

Comparison of two supporting matrices for patient-derived cancer cells in 3D drug sensitivity and resistance testing assay (3D-DSRT).

Central to the success of functional precision medicine of solid tumors is to perform drug testing of patient-derived cancer cells (PDCs) in tumor-mimicking ex vivo conditions. While high throughput (HT) drug screening methods have been well-established for cells cultured in two-dimensional (2D) format, this approach may have limited value in predicting clinical responses. Here, we describe the results of the optimization of drug sensitivity and resistance testing (DSRT) in three-dimensional (3D) growth supporting matrices in a HT mode (3D-DSRT) using the hepatocyte cell line (HepG2) as an example. Supporting matrices included widely used animal-derived Matrigel and cellulose-based hydrogel, GrowDex, which has earlier been shown to support 3D growth of cell lines and stem cells. Further, the sensitivity of ovarian cancer PDCs, from two patients included in the functional precision medicine study, was tested for 52 drugs in 5 different concentrations using 3D-DSRT. Shortly, in the optimized protocol, the PDCs are embedded with matrices and seeded to 384-well plates to allow the formation of the spheroids prior to the addition of drugs in nanoliter volumes with acoustic dispenser. The sensitivity of spheroids to drug treatments is measured with cell viability readout (here, 72 h after addition of drugs). The quality control and data analysis are performed with openly available Breeze software. We show the usability of both matrices in established 3D-DSRT, and report 2D vs 3D growth condition dependent differences in sensitivities of ovarian cancer PDCs to MEK-inhibitors and cytotoxic drugs. This study provides a proof-of-concept for robust and fast screening of drug sensitivities of PDCs in 3D-DSRT, which is important not only for drug discovery but also for personalized ex vivo drug testing in functional precision medicine studies. These findings suggest that comparing results of 2D- and 3D-DSRT is essential for understanding drug mechanisms and for selecting the most effective treatment for the patient.

Protocol for 3D drug sensitivity and resistance testing of patient-derived cancer cells in 384-well plates.

Establishment of drug testing of patient-derived cancer cells (PDCs) in physiologically relevant 3-dimensional (3D) culture is central for drug discovery and cancer research, as well as for functional precision medicine. Here, we describe the detailed protocol allowing the 3D drug testing of PDCs - or any type of cells of interest - in Matrigel in 384-well plate format using automation. We also provide an alternative protocol, which does not require supporting matrices. The cancer tissue is obtained directly from clinics (after surgery or biopsy) and processed into single cell suspension. Systematic drug sensitivity and resistance testing (DSRT) is carried out on the PDCs directly after cancer cell isolation from tissue or on cells expanded for a few passages. In the 3D-DSRT assay, the PDCs are plated in 384-well plates in Matrigel, grown as spheroids, and treated with compounds of interest for 72 h. The cell viability is directly measured using a luminescence-based assay. Alternatively, prior to the cell viability measurement, drug-treated cells can be directly subjected to automated high-content bright field imaging or stained for fluorescence (live) cell microscopy for further image analysis. This is followed by the quality control and data analysis. The 3D-DSRT can be performed within a 1-3-week timeframe of the clinical sampling of cancer tissue, depending on the amount of the obtained tissue, growth rate of cancer cells, and the number of drugs being tested. The 3D-DSRT method can be flexibly modified, e.g., to be carried out with or without supporting matrices with U-bottom 384-well plates when appropriate for the PDCs or other cell models used.

Drug sensitivity profiling of 3D tumor tissue cultures in the pediatric precision oncology program INFORM.

The international precision oncology program INFORM enrolls relapsed/refractory pediatric cancer patients for comprehensive molecular analysis. We report a two-year pilot study implementing ex vivo drug sensitivity profiling (DSP) using a library of 75-78 clinically relevant drugs. We included 132 viable tumor samples from 35 pediatric oncology centers in seven countries. DSP was conducted on multicellular fresh tumor tissue spheroid cultures in 384-well plates with an overall mean processing time of three weeks. In 89 cases (67%), sufficient viable tissue was received; 69 (78%) passed internal quality controls. The DSP results matched the identified molecular targets, including BRAF, ALK, MET, and TP53 status. Drug vulnerabilities were identified in 80% of cases lacking actionable (very) high-evidence molecular events, adding value to the molecular data. Striking parallels between clinical courses and the DSP results were observed in selected patients. Overall, DSP in clinical real-time is feasible in international multicenter precision oncology programs.

iTReX: Interactive exploration of mono- and combination therapy dose response profiling data.

High throughput screening methods, measuring the sensitivity and resistance of tumor cells to drug treatments have been rapidly evolving. Not only do these screens allow correlating response profiles to tumor genomic features for developing novel predictors of treatment response, but they can also add evidence for therapy decision making in precision oncology. Recent analysis methods developed for either assessing single agents or combination drug efficacies enable quantification of dose-response curves with restricted symmetric fit settings. Here, we introduce iTReX, a user-friendly and interactive Shiny/R application, for both the analysis of mono- and combination therapy responses. The application features an extended version of the drug sensitivity score (DSS) based on the integral of an advanced five-parameter dose-response curve model and a differential DSS for combination therapy profiling. Additionally, iTReX includes modules that visualize drug target interaction networks and support the detection of matches between top therapy hits and the sample omics features to enable the identification of druggable targets and biomarkers. iTReX enables the analysis of various quantitative drug or therapy response readouts (e.g. luminescence, fluorescence microscopy) and multiple treatment strategies (drug treatments, radiation). Using iTReX we validate a cost-effective drug combination screening approach and reveal the application's ability to identify potential sample-specific biomarkers based on drug target interaction networks. The iTReX web application is accessible at https://itrex.kitz-heidelberg.de.

Implementing a Functional Precision Medicine Tumor Board for Acute Myeloid Leukemia.

We generated ex vivo drug-response and multiomics profiling data for a prospective series of 252 samples from 186 patients with acute myeloid leukemia (AML). A functional precision medicine tumor board (FPMTB) integrated clinical, molecular, and functional data for application in clinical treatment decisions. Actionable drugs were found for 97% of patients with AML, and the recommendations were clinically implemented in 37 relapsed or refractory patients. We report a 59% objective response rate for the individually tailored therapies, including 13 complete responses, as well as bridging five patients with AML to allogeneic hematopoietic stem cell transplantation. Data integration across all cases enabled the identification of drug response biomarkers, such as the association of IL15 overexpression with resistance to FLT3 inhibitors. Integration of molecular profiling and large-scale drug response data across many patients will enable continuous improvement of the FPMTB recommendations, providing a paradigm for individualized implementation of functional precision cancer medicine. SIGNIFICANCE: Oncogenomics data can guide clinical treatment decisions, but often such data are neither actionable nor predictive. Functional ex vivo drug testing contributes significant additional, clinically actionable therapeutic insights for individual patients with AML. Such data can be generated in four days, enabling rapid translation through FPMTB.See related commentary by Letai, p. 290.This article is highlighted in the In This Issue feature, p. 275.

High-throughput compound screening identifies navitoclax combined with irradiation as a candidate therapy for HPV-negative head and neck squamous cell carcinoma.

Conventional chemotherapeutic agents are nonselective, often resulting in severe side effects and the development of resistance. Therefore, new molecular-targeted therapies are urgently needed to be integrated into existing treatment regimens. Here, we performed a high-throughput compound screen to identify a synergistic interaction between ionizing radiation and 396 anticancer compounds. The assay was run using five human papillomavirus (HPV)-negative head and neck squamous cell carcinoma (HNSCC) cell lines cultured on the human tumor-derived matrix Myogel. Our screen identified several compounds with strong synergistic and antagonistic effects, which we further investigated using multiple irradiation doses. Navitoclax, which emerged as the most promising radiosensitizer, exhibited synergy with irradiation regardless of the p53 mutation status in all 13 HNSCC cell lines. We performed a live cell apoptosis assay for two representative HNSCC cell lines to examine the effects of navitoclax and irradiation. As a single agent, navitoclax reduced proliferation and induced apoptosis in a dose-dependent manner, whereas the navitoclax-irradiation combination arrested cell cycle progression and resulted in substantially elevated apoptosis. Overall, we demonstrated that combining navitoclax with irradiation resulted in synergistic in vitro antitumor effects in HNSCC cell lines, possibly indicating the therapeutic potential for HNSCC patients.

Patient-tailored design for selective co-inhibition of leukemic cell subpopulations.

The extensive drug resistance requires rational approaches to design personalized combinatorial treatments that exploit patient-specific therapeutic vulnerabilities to selectively target disease-driving cell subpopulations. To solve the combinatorial explosion challenge, we implemented an effective machine learning approach that prioritizes patient-customized drug combinations with a desired synergy-efficacy-toxicity balance by combining single-cell RNA sequencing with ex vivo single-agent testing in scarce patient-derived primary cells. When applied to two diagnostic and two refractory acute myeloid leukemia (AML) patient cases, each with a different genetic background, we accurately predicted patient-specific combinations that not only resulted in synergistic cancer cell co-inhibition but also were capable of targeting specific AML cell subpopulations that emerge in differing stages of disease pathogenesis or treatment regimens. Our functional precision oncology approach provides an unbiased means for systematic identification of personalized combinatorial regimens that selectively co-inhibit leukemic cells while avoiding inhibition of nonmalignant cells, thereby increasing their likelihood for clinical translation.

Drug screening approach combines epigenetic sensitization with immunochemotherapy in cancer.

BACKGROUND: The epigenome plays a key role in cancer heterogeneity and drug resistance. Hence, a number of epigenetic inhibitors have been developed and tested in cancers. The major focus of most studies so far has been on the cytotoxic effect of these compounds, and only few have investigated the ability to revert the resistant phenotype in cancer cells. Hence, there is a need for a systematic methodology to unravel the mechanisms behind epigenetic sensitization. RESULTS: We have developed a high-throughput protocol to screen non-simultaneous drug combinations, and used it to investigate the reprogramming potential of epigenetic inhibitors. We demonstrated the effectiveness of our protocol by screening 60 epigenetic compounds on diffuse large B-cell lymphoma (DLBCL) cells. We identified several histone deacetylase (HDAC) and histone methyltransferase (HMT) inhibitors that acted synergistically with doxorubicin and rituximab. These two classes of epigenetic inhibitors achieved sensitization by disrupting DNA repair, cell cycle, and apoptotic signaling. The data used to perform these analyses are easily browsable through our Results Explorer. Additionally, we showed that these inhibitors achieve sensitization at lower doses than those required to induce cytotoxicity. CONCLUSIONS: Our drug screening approach provides a systematic framework to test non-simultaneous drug combinations. This methodology identified HDAC and HMT inhibitors as successful sensitizing compounds in treatment-resistant DLBCL. Further investigation into the mechanisms behind successful epigenetic sensitization highlighted DNA repair, cell cycle, and apoptosis as the most dysregulated pathways. Altogether, our method adds supporting evidence in the use of epigenetic inhibitors as sensitizing agents in clinical settings.

Human Tumor-Derived Matrix Improves the Predictability of Head and Neck Cancer Drug Testing.

In vitro cancer drug testing carries a low predictive value. We developed the human leiomyoma-derived matrix "Myogel" to better mimic the human tumor microenvironment (TME). We hypothesized that Myogel could provide an appropriate microenvironment for cancer cells, thereby allowing more in vivo-relevant drug testing. We screened 19 anticancer compounds, targeting the epidermal growth factor receptor (EGFR), MEK, and PI3K/mTOR on 12 head and neck squamous cell carcinoma (HNSCC) cell lines cultured on plastic, mouse sarcoma-derived Matrigel (MSDM), and Myogel. We applied a high-throughput drug screening assay under five different culturing conditions: cells in two-dimensional (2D) plastic wells and on top or embedded in Matrigel or Myogel. We then compared the efficacy of the anticancer compounds to the response rates of 19 HNSCC monotherapy clinical trials. Cancer cells on top of Myogel responded less to EGFR and MEK inhibitors compared to cells cultured on plastic or Matrigel. However, we found a similar response to the PI3K/mTOR inhibitors under all culturing conditions. Cells grown on Myogel more closely resembled the response rates reported in EGFR-inhibitor monotherapy clinical trials. Our findings suggest that a human tumor matrix improves the predictability of in vitro anticancer drug testing compared to current 2D and MSDM methods.

Methods for High-throughput Drug Combination Screening and Synergy Scoring.

Gene products or pathways that are aberrantly activated in cancer but not in normal tissue hold great promises for being effective and safe anticancer therapeutic targets. Many targeted drugs have entered clinical trials but so far showed limited efficacy mostly due to variability in treatment responses and often rapidly emerging resistance. Toward more effective treatment options, we will need multi-targeted drugs or drug combinations, which selectively inhibit the viability and growth of cancer cells and block distinct escape mechanisms for the cells to become resistant. Functional profiling of drug combinations requires careful experimental design and robust data analysis approaches. At the Institute for Molecular Medicine Finland (FIMM), we have developed an experimental-computational pipeline for high-throughput screening of drug combination effects in cancer cells. The integration of automated screening techniques with advanced synergy scoring tools allows for efficient and reliable detection of synergistic drug interactions within a specific window of concentrations, hence accelerating the identification of potential drug combinations for further confirmatory studies.

Antiviral Properties of Chemical Inhibitors of Cellular Anti-Apoptotic Bcl-2 Proteins.

Viral diseases remain serious threats to public health because of the shortage of effective means of control. To combat the surge of viral diseases, new treatments are urgently needed. Here we show that small-molecules, which inhibit cellular anti-apoptotic Bcl-2 proteins (Bcl-2i), induced the premature death of cells infected with different RNA or DNA viruses, whereas, at the same concentrations, no toxicity was observed in mock-infected cells. Moreover, these compounds limited viral replication and spread. Surprisingly, Bcl-2i also induced the premature apoptosis of cells transfected with viral RNA or plasmid DNA but not of mock-transfected cells. These results suggest that Bcl-2i sensitizes cells containing foreign RNA or DNA to apoptosis. A comparison of the toxicity, antiviral activity, and side effects of six Bcl-2i allowed us to select A-1155463 as an antiviral lead candidate. Thus, our results pave the way for the further development of Bcl-2i for the prevention and treatment of viral diseases.

Precision Cancer Medicine in the Acoustic Dispensing Era: Ex Vivo Primary Cell Drug Sensitivity Testing.

Cancer therapy is increasingly becoming individualized, but there are also big gaps between the molecular knowledge of individual cancers we can generate today and what can be applied in the clinic. In an attempt to bridge this knowledge gap between cancer genetic and molecular profiling and clinically useful information, an individualized systems medicine program has been established at the Institute for Molecular Medicine Finland (FIMM), University of Helsinki, and the Helsinki University Hospital. Central to this program is drug sensitivity and resistance testing (DSRT), in which responses of primary cancer cells to a comprehensive clinical oncology and signal transduction drug collection are monitored. The drug sensitivity information is used with molecular profiling to establish hypotheses on individual cancer-selective targeting drug combinations and their predictive biomarkers, which can be explored in the clinic. Here, we describe how acoustic droplet ejection is enabling DSRT in our cancer individualized systems medicine program to (1) generate consistent but configurable assay-ready plates and determine how this affects data quality, (2) flexibly prepare drug combination testing plates, (3) dispense reagents and cells to the assay plates, and (4) perform ultra-miniaturized follow-up assays on the cells from DSRT plates.

Systematic Mapping of Kinase Addiction Combinations in Breast Cancer Cells by Integrating Drug Sensitivity and Selectivity Profiles.

Chemical perturbation screens offer the possibility to identify actionable sets of cancer-specific vulnerabilities. However, most inhibitors of kinases or other cancer targets result in polypharmacological effects, which complicate the identification of target dependencies directly from the drug-response phenotypes. In this study, we developed a chemical systems biology approach that integrates comprehensive drug sensitivity and selectivity profiling to provide functional insights into both single and multi-target oncogenic signal addictions. When applied to 21 breast cancer cell lines, perturbed with 40 kinase inhibitors, the subtype-specific addiction patterns clustered in agreement with patient-derived subtypes, while showing considerable variability between the heterogeneous breast cancers. Experimental validation of the top predictions revealed a number of co-dependencies between kinase targets that led to unexpected synergistic combinations between their inhibitors, such as dasatinib and axitinib in the triple-negative basal-like HCC1937 cell line.

Discovery of MINC1, a GTPase-activating protein small molecule inhibitor, targeting MgcRacGAP.

The Rho family of Ras superfamily small GTPases regulates a broad range of biological processes such as migration, differentiation, cell growth and cell survival. Therefore, the availability of small molecule modulators as tool compounds could greatly enhance research on these proteins and their biological function. To this end, we designed a biochemical, high throughput screening assay with complementary follow-up assays to identify small molecule compounds inhibiting MgcRacGAP, a Rho family GTPase activating protein involved in cytokinesis and transcriptionally upregulated in many cancers. We first performed an in-house screen of 20,480 compounds, and later we tested the assay against 342,046 compounds from the NIH Molecular Libraries Small Molecule Repository. Primary screening hit rates were about 1% with the majority of those affecting the primary readout, an enzyme-coupled GDP detection assay. After orthogonal and counter screens, we identified two hits with high selectivity towards MgcRacGAP, compared with other RhoGAPs, and potencies in the low micromolar range. The most promising hit, termed MINC1, was then examined with cell-based testing where it was observed to induce an increased rate of cytokinetic failure and multinucleation in addition to other cell division defects, suggesting that it may act as an MgcRacGAP inhibitor also in cells.

The high throughput biomedicine unit at the institute for molecular medicine Finland: high throughput screening meets precision medicine.

The High Throughput Biomedicine (HTB) unit at the Institute for Molecular Medicine Finland FIMM was established in 2010 to serve as a national and international academic screening unit providing access to state of the art instrumentation for chemical and RNAi-based high throughput screening. The initial focus of the unit was multiwell plate based chemical screening and high content microarray-based siRNA screening. However, over the first four years of operation, the unit has moved to a more flexible service platform where both chemical and siRNA screening is performed at different scales primarily in multiwell plate-based assays with a wide range of readout possibilities with a focus on ultraminiaturization to allow for affordable screening for the academic users. In addition to high throughput screening, the equipment of the unit is also used to support miniaturized, multiplexed and high throughput applications for other types of research such as genomics, sequencing and biobanking operations. Importantly, with the translational research goals at FIMM, an increasing part of the operations at the HTB unit is being focused on high throughput systems biological platforms for functional profiling of patient cells in personalized and precision medicine projects.

Utilization of in situ ELISA method for examining Trk receptor phosphorylation in cultured cells.

BACKGROUND: Trk receptor tyrosine kinases regulate multiple important neuronal processes during the development and in the adulthood. Tyrosine phosphorylation of Trk serves as the initial step in the Trk signaling pathway and indicates receptor' autocatalytic activity. However, methods allowing simple and large-scale Trk phosphorylation analyses in cultured cells are lacking. NEW METHOD: We describe an in situ phospho-Trk ELISA (enzyme-linked immunosorbent assay) method where cell culture, receptor stimulation and Trk phosphorylation analysis are all performed on the same multiwell plate. RESULTS: In situ phospho-Trk ELISA readily and specifically detects neurotrophin-induced Trk phosphorylation in cultured cells. A proof-of-concept small molecule screening of a library composed of 2000 approved drugs and other bioactive compounds was carried out using this novel method. COMPARISON WITH EXISTING METHODS: In situ phospho-Trk ELISA utilizes the principles and advantages of conventional sandwich ELISA in an in situ context. CONCLUSIONS: We describe a novel method that can be efficiently used to examine Trk receptor phosphorylation in cultured cells. Principally similar methods can be developed to examine the levels and signaling of any intracellular protein.

Individualized systems medicine strategy to tailor treatments for patients with chemorefractory acute myeloid leukemia.

UNLABELLED: We present an individualized systems medicine (ISM) approach to optimize cancer drug therapies one patient at a time. ISM is based on (i) molecular profiling and ex vivo drug sensitivity and resistance testing (DSRT) of patients' cancer cells to 187 oncology drugs, (ii) clinical implementation of therapies predicted to be effective, and (iii) studying consecutive samples from the treated patients to understand the basis of resistance. Here, application of ISM to 28 samples from patients with acute myeloid leukemia (AML) uncovered five major taxonomic drug-response subtypes based on DSRT profiles, some with distinct genomic features (e.g., MLL gene fusions in subgroup IV and FLT3-ITD mutations in subgroup V). Therapy based on DSRT resulted in several clinical responses. After progression under DSRT-guided therapies, AML cells displayed significant clonal evolution and novel genomic changes potentially explaining resistance, whereas ex vivo DSRT data showed resistance to the clinically applied drugs and new vulnerabilities to previously ineffective drugs. SIGNIFICANCE: Here, we demonstrate an ISM strategy to optimize safe and effective personalized cancer therapies for individual patients as well as to understand and predict disease evolution and the next line of therapy. This approach could facilitate systematic drug repositioning of approved targeted drugs as well as help to prioritize and de-risk emerging drugs for clinical testing.