Article Figures & Data
Figures
- Fig. 1.
Schematic process demonstrating project filtering. CDs selected during 50 years of R&D at the AstraZeneca CVGI therapy area were filtered for second-generation molecules and nonefficacy-based attrition, and whether the efficacy readout was generated prior to the retrospective evaluation of the 10-point HTV classification with regard to its ability to predict future clinical efficacy of a CD.
- Fig. 2.
HTV assessment: relationship of HTV status to clinical efficacy and portfolio impact of applying HTV strategies. (A) Historical HTV status at the time of CD selection. A retrospective evaluation of HTV for all CDs that entered into human studies of sufficient length to generate efficacy readouts in the past 50 years within AstraZeneca’s CVGI therapy area. Data show HTV status at the time of CD selection and relationship to clinical efficacy. The number of projects in each group can be found in Fig. 1. (B) Portfolio impact of developing and applying HTV strategies. Application of HTV strategies to projects resulted in a decrease in the percentage of projects with low HTV status, an increase in the percentage of projects with medium HTV status, and no change in the overall proportion of projects with high HTV status over a period of 18 months and beyond.
Tables
HTV Definition High HTV Level 1 Drug is on the market 1.1 Mortality/morbidity endpoint met in target population 1.2 Surrogate endpoint (approvable) met in target population 1.3 Confidence-generating endpoints met in target population Level 2 Clinical tool is hitting the target 2.1 Surrogate endpoint (approvable) met in target population 2.2 Confidence-generating endpoints met in target population Level 3 Drug is hitting a target in the pathway of interest 3.1 Mortality/morbidity endpoint met in target population 3.2 Surrogate endpoint (approvable) met in target population 3.3 Confidence-generating endpoints met in target population Level 4 Drug/clinical tool is hitting the target and/or pathway outside the target population 4.1 Surrogate endpoint (approvable) met 4.2 Confidence-generating endpoints met Medium HTV Level 5 Phenotypes/genotypes in the diseased state have been identified 5.1 Extreme (for example, naturally occurring mutants) 5.2 Heterogeneous (for example, based on population databases, patient cohorts) Level 6 Clinical challenge model 6.1 Nondrug; stress test of pathway (for example, fat meal, lipopolysaccharide [LPS] challenge) Level 7 Target affected in human ex vivo tissue manipulation 7.1 For example, platelet ADP stimulation, insulin secretion from human islets Low HTV Level 8 Target/target pathway is altered in healthy vs. diseased population 8.1 For example, positron emission tomography tracer data supportive, bioinformatics, in silico mapping Level 9 Target of interest is present in correct tissue/cell type 9.1 For example, bioinformatics, experimental evidence Level 10 No relevant human data Timescale Project Start 6 mo 12 mo 18+ mo HTV status Low (level 9) Low (level 8) Medium (level 6) High (level 2) Target present in correct tissue Target/pathway is altered in healthy vs. diseased population Pathway-related effect in clinical challenge model Clinical tool is hitting the target Evidence mRNA expression data demonstrated GPR103 expression in human brain, including the hypothalamus, and QRFP (endogenous ligand) expression and binding in human hypothalamic neurons Key activities Is there evidence that the GPR103 pathway and/or its ligands are dysregulated in obese patients (in silico analysis of internal and external databases)? Is there evidence that the GPR103 receptor ligands QRFP26 and QRFP43 are present in either the circulation or cerebrospinal fluid at different levels in humans between fasting and fed states? Does an exploratory clinical tool GPR103 antagonist reduce food intake in humans? QRFP, pyroglutamylated RFamide peptide.
