scholarly journals Flipping the odds of drug development success through human genomics

2017 ◽  
Author(s):  
Aroon D. Hingorani ◽  
Valerie Kuan ◽  
Chris Finan ◽  
Felix A. Kruger ◽  
Anna Gaulton ◽  
...  
Keyword(s):  
Monoclonal Antibodies ◽  
Drug Development ◽  
Drug Target ◽  
Molecular Targets ◽  
Pharmacological Action ◽  
Common Disease ◽  
Human Genomics ◽  
Small Molecule Drugs ◽  
Development Failure ◽  
Druggable Targets

AbstractDrug development depends on accurately identifying molecular targets that both play a causal role in a disease and are amenable to pharmacological action by small molecule drugs or bio-therapeutics, such as monoclonal antibodies.Errors in drug target specification contribute to the extremely high rates of drug development failure.Integrating knowledge of genes that encode druggable targets with those that influence susceptibility to common disease has the potential to radically improve the probability of drug development success.

scholarly journals Improving the odds of drug development success through human genomics: modelling study

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Aroon D. Hingorani ◽  
Valerie Kuan ◽  
Chris Finan ◽  
Felix A. Kruger ◽  
Anna Gaulton ◽  
...  
Keyword(s):  
Drug Development ◽  
Target Identification ◽  
Preclinical Studies ◽  
Success Rates ◽  
Protein Coding ◽  
Human Genomics ◽  
Genome Wide ◽  
Drug Target Identification ◽  
Development Failure

AbstractLack of efficacy in the intended disease indication is the major cause of clinical phase drug development failure. Explanations could include the poor external validity of pre-clinical (cell, tissue, and animal) models of human disease and the high false discovery rate (FDR) in preclinical science. FDR is related to the proportion of true relationships available for discovery (γ), and the type 1 (false-positive) and type 2 (false negative) error rates of the experiments designed to uncover them. We estimated the FDR in preclinical science, its effect on drug development success rates, and improvements expected from use of human genomics rather than preclinical studies as the primary source of evidence for drug target identification. Calculations were based on a sample space defined by all human diseases – the ‘disease-ome’ – represented as columns; and all protein coding genes – ‘the protein-coding genome’– represented as rows, producing a matrix of unique gene- (or protein-) disease pairings. We parameterised the space based on 10,000 diseases, 20,000 protein-coding genes, 100 causal genes per disease and 4000 genes encoding druggable targets, examining the effect of varying the parameters and a range of underlying assumptions, on the inferences drawn. We estimated γ, defined mathematical relationships between preclinical FDR and drug development success rates, and estimated improvements in success rates based on human genomics (rather than orthodox preclinical studies). Around one in every 200 protein-disease pairings was estimated to be causal (γ = 0.005) giving an FDR in preclinical research of 92.6%, which likely makes a major contribution to the reported drug development failure rate of 96%. Observed success rate was only slightly greater than expected for a random pick from the sample space. Values for γ back-calculated from reported preclinical and clinical drug development success rates were also close to the a priori estimates. Substituting genome wide (or druggable genome wide) association studies for preclinical studies as the major information source for drug target identification was estimated to reverse the probability of late stage failure because of the more stringent type 1 error rate employed and the ability to interrogate every potential druggable target in the same experiment. Genetic studies conducted at much larger scale, with greater resolution of disease end-points, e.g. by connecting genomics and electronic health record data within healthcare systems has the potential to produce radical improvement in drug development success rate.

Old Drugs with New Tricks; Paradigm in Drug Development Pipeline for Alzheimer’s Disease

2020 ◽  
Vol 20 ◽  
Author(s):  
Tanay Dalvi ◽  
Bhaskar Dewangan ◽  
Rudradip Das ◽  
Jyoti Rani ◽  
Suchita Dattatray Shinde ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Drug Development ◽  
Molecular Targets ◽  
Drug Repurposing ◽  
Phase Iii ◽  
Complex Nature ◽  
New Drug ◽  
Development Pipeline ◽  
Old Drugs

: The most common reason behind dementia is Alzheimer’s disease (AD) and it is predicted to be the third lifethreatening disease apart from stroke and cancer for the geriatric population. Till now only four drugs are available in the market for symptomatic relief. The complex nature of disease pathophysiology and lack of concrete evidences of molecular targets are the major hurdles for developing new drug to treat AD. The the rate of attrition of many advanced drugs at clinical stages, makes the de novo discovery process very expensive. Alternatively, Drug Repurposing (DR) is an attractive tool to develop drugs for AD in a less tedious and economic way. Therefore, continuous efforts are being made to develop a new drug for AD by repursing old drugs through screening and data mining. For example, the survey in the drug pipeline for Phase III clinical trials (till February 2019) which has 27 candidates, and around half of the number are drugs which have already been approved for other indications. Although in the past the drug repurposing process for AD has been reviewed in the context of disease areas, molecular targets, there is no systematic review of repurposed drugs for AD from the recent drug development pipeline (2019-2020). In this manuscript, we are reviewing the clinical candidates for AD with emphasis on their development history including molecular targets and the relevance of the target for AD.

scholarly journals Alternative approaches to target Myc for cancer treatment

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Chen Wang ◽  
Jiawei Zhang ◽  
Jie Yin ◽  
Yichao Gan ◽  
Senlin Xu ◽  
...  
Keyword(s):  
Cancer Treatment ◽  
Small Molecules ◽  
Drug Target ◽  
The Past ◽  
Physiological Processes ◽  
Alternative Approaches ◽  
Global Transcriptome ◽  
Factor C ◽  
Signaling Modules ◽  
Druggable Targets

AbstractThe Myc proto-oncogene family consists of three members, C-MYC, MYCN, and MYCL, which encodes the transcription factor c-Myc (hereafter Myc), N-Myc, and L-Myc, respectively. Myc protein orchestrates diverse physiological processes, including cell proliferation, differentiation, survival, and apoptosis. Myc modulates about 15% of the global transcriptome, and its deregulation rewires the cellular signaling modules inside tumor cells, thereby acquiring selective advantages. The deregulation of Myc occurs in >70% of human cancers, and is related to poor prognosis; hence, hyperactivated Myc oncoprotein has been proposed as an ideal drug target for decades. Nevertheless, no specific drug is currently available to directly target Myc, mainly because of its “undruggable” properties: lack of enzymatic pocket for conventional small molecules to bind; inaccessibility for antibody due to the predominant nucleus localization of Myc. Although the topic of targeting Myc has actively been reviewed in the past decades, exciting new progresses in this field keep emerging. In this review, after a comprehensive summarization of valuable sources for potential druggable targets of Myc-driven cancer, we also peer into the promising future of utilizing macropinocytosis to deliver peptides like Omomyc or antibody agents to intracellular compartment for cancer treatment.

scholarly journals The Use, Standardization, and Interpretation of Brain Imaging Data in Clinical Trials of Neurodegenerative Disorders

2021 ◽  
Author(s):  
Adam J. Schwarz
Keyword(s):  
Clinical Trials ◽  
Drug Development ◽  
Neurological Disorders ◽  
Amyloid Β ◽  
Development Program ◽  
Imaging Biomarkers ◽  
Common Disease ◽  
Structural Imaging ◽  
Target Engagement ◽  
Pharmacodynamic Effect

AbstractImaging biomarkers play a wide-ranging role in clinical trials for neurological disorders. This includes selecting the appropriate trial participants, establishing target engagement and mechanism-related pharmacodynamic effect, monitoring safety, and providing evidence of disease modification. In the early stages of clinical drug development, evidence of target engagement and/or downstream pharmacodynamic effect—especially with a clear relationship to dose—can provide confidence that the therapeutic candidate should be advanced to larger and more expensive trials, and can inform the selection of the dose(s) to be further tested, i.e., to “de-risk” the drug development program. In these later-phase trials, evidence that the therapeutic candidate is altering disease-related biomarkers can provide important evidence that the clinical benefit of the compound (if observed) is grounded in meaningful biological changes. The interpretation of disease-related imaging markers, and comparability across different trials and imaging tools, is greatly improved when standardized outcome measures are defined. This standardization should not impinge on scientific advances in the imaging tools per se but provides a common language in which the results generated by these tools are expressed. PET markers of pathological protein aggregates and structural imaging of brain atrophy are common disease-related elements across many neurological disorders. However, PET tracers for pathologies beyond amyloid β and tau are needed, and the interpretability of structural imaging can be enhanced by some simple considerations to guard against the possible confound of pseudo-atrophy. Learnings from much-studied conditions such as Alzheimer’s disease and multiple sclerosis will be beneficial as the field embraces rarer diseases.

scholarly journals Plasmodium falciparum: new molecular targets with potential for antimalarial drug development

2009 ◽  
Vol 7 (9) ◽  
pp. 1087-1098 ◽  
Author(s):  
Donald L Gardiner ◽  
Tina S Skinner-Adams ◽  
Christopher L Brown ◽  
Katherine T Andrews ◽  
Colin M Stack ◽  
...  
Keyword(s):  
Plasmodium Falciparum ◽  
Drug Development ◽  
Antimalarial Drug ◽  
Molecular Targets ◽  
New Molecular Targets

scholarly journals Drug target gene-based analyses of drug repositionability in rare and intractable diseases

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ryuichi Sakate ◽  
Tomonori Kimura
Keyword(s):  
Drug Development ◽  
Drug Target ◽  
Target Gene ◽  
Target Genes ◽  
Drug Information ◽  
Drug Repositioning ◽  
Clinical Trial Data ◽  
Insufficient Information ◽  
Disease Pair ◽  
Low Prevalence

AbstractDrug development for rare and intractable diseases has been challenging for decades due to the low prevalence and insufficient information on these diseases. Drug repositioning is increasingly being used as a promising option in drug development. We aimed to analyze the trend of drug repositioning and inter-disease drug repositionability among rare and intractable diseases. We created a list of rare and intractable diseases based on the designated diseases in Japan. Drug information extracted from clinical trial data were integrated with information of drug target genes, which represent the mechanism of drug action. We obtained 753 drugs and 551 drug target genes from 8307 clinical trials for 189 diseases or disease groups. Trend analysis of drug sharing between a disease pair revealed that 1676 drug repositioning events occurred in 4401 disease pairs. A score, Rgene, was invented to investigate the proportion of drug target genes shared between a disease pair. Annual changes of Rgene corresponded to the trend of drug repositioning and predicted drug repositioning events occurring within a year or two. Drug target gene-based analyses well visualized the drug repositioning landscape. This approach facilitates drug development for rare and intractable diseases.

The Economics of New Drugs: Can We Afford to Make Progress in a Common Disease?

2013 ◽  
pp. e126-e130
Author(s):  
Bradford R. Hirsch ◽  
Kevin A. Schulman
Keyword(s):  
Drug Development ◽  
Cost Of Capital ◽  
New Drugs ◽  
Common Disease ◽  
Target Market ◽  
Sustainable Business ◽  
Product Pricing ◽  
Grant Support ◽  
To Come ◽  
The Cost

The concept of personalized medicine is beginning to come to fruition, but the cost of drug development is untenable today. To identify new initiatives that would support a more sustainable business model, the economics of drug development are analyzed, including the cost of drug development, cost of capital, target market size, returns to innovators at the product and firm levels, and, finally, product pricing. We argue that a quick fix is not available. Instead, a rethinking of the entire pharmaceutical development process is needed from the way that clinical trials are conducted, to the role of biomarkers in segmenting markets, to the use of grant support, and conditional approval to decrease the cost of capital. In aggregate, the opportunities abound.

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