Fixing a broken drug development process

2013 ◽  
Vol 19 (1) ◽  
Author(s):  
John Holland
Keyword(s):  
Drug Discovery ◽  
Development Process ◽  
Pharmaceutical Research ◽  
New Drugs ◽  
Washington Dc ◽  
Drug Development Process ◽  
Drug Trials ◽  
Low Levels ◽  
The Cost ◽  
The U.S

It costs about $1.2 billion to bring a single new drug to market in the U.S. today.[1] With a combination of high late-stage failure rates and the high cost of drug trials, the number of new drugs being approved by the FDA has flat-lined at historically low levels, falling from 53 in 1996 to just 19 in 2009.[2] If the cost of drug trials doesn’t come down, we will see far fewer new drugs on pharmacy shelves. [1] Pharmaceutical Research and Manufacturers of America Profile 2009. Washington, DC: PhRMA. [2] Hughes B. 2009 Drug Approvals. Nature Reviews Drug Discovery 9, 89-92 (February 2010)

scholarly journals SMALL MOLECULES SOLVING BIG PROBLEMS: PRESENT AND FUTURE OF DRUG DISCOVERY

2018 ◽  
Vol 9 (1) ◽  
Author(s):  
Anna Lucia Fallacara ◽  
Iuni Margaret Laura Tris ◽  
Amalia Belfiore ◽  
Maurizio Botta
Keyword(s):  
Drug Discovery ◽  
Drug Development ◽  
Small Molecules ◽  
Rational Design ◽  
Development Process ◽  
New Drugs ◽  
Drug Development Process ◽  
Development Models ◽  
The Past ◽  
The Cost

The Drug development process has undergone a great change over the years. The way, from haphazard discovery of new natural products with a potent biological activity to a rational design of small molecule effective against a selected target, has been long and sprinkled with difficulties. The oldest drug development models are widely perceived as opaque and inefficient, with the cost of research and development continuing to rise even if the production of new drugs remains constant. The present paper, will give an overview of the principles, approaches, processes, and status of drug discovery today with an eye towards the past and the future.

Significant role of chemistry in drug development: a systematic journey from traditional to modern approaches with anti-HIV/AIDS drugs as examples

2021 ◽  
Vol 27 ◽  
Author(s):  
Madhu Yadav ◽  
Ritika Srivastava ◽  
Farha Naaz ◽  
Rajesh Verma ◽  
Ramendra K. Singh
Keyword(s):  
Drug Discovery ◽  
Drug Development ◽  
Development Process ◽  
New Drugs ◽  
Computer Assisted ◽  
Synthetic Chemistry ◽  
Drug Development Process ◽  
Drug Molecules ◽  
Hiv Aids

Background: Traditionally, various plant extracts having interesting biological properties were the main source of new drugs. In the last 30 years, the role of chemistry in combination with new technologies, like various computational techniques in chemistry, has witnessed a major upsurge in drug discovery and targeted drug delivery. Objective: This article provides a succinct overview of recent techniques of chemistry that have a great impact on the drug development process in general and also against HIV/AIDS. It focuses on new methods employed for drug development with an emphasis on in silico studies, including identifying drug targets, especially the proteins associated with specific diseases. Methods: The rational drug development process starts with the identification of a drug target as the first phase, which helps in the computer-assisted design of new drug molecules. Synthetic chemistry has a major impact on the drug development process because it provides new molecules for future study. Natural products based semisynthesis or microwave assisted synthesis is also involved in developing newly designed drug molecules. Further, the role of analytical chemistry involves extraction, fractionation, isolation and characterization of newly synthesized molecules. Results: Chemistry plays a key role in drug discovery and delivery by natural process or with the help of synthetic nanoparticles or nanomedicines. So, nanochemistry is also deeply involved in the development of new drugs and their applications. Conclusion: The previous era of drug discovery was dominated only by chemistry, but the modern approaches involve a comprehensive knowledge of synthetic chemistry, medicinal chemistry, computational chemistry and the concerned biological phenomenon.

scholarly journals Biomarkers and Surrogate Endpoints: How and When might They Impact Drug Development?

2002 ◽  
Vol 18 (2) ◽  
pp. 83-90 ◽  
Author(s):  
Chetan D. Lathia
Keyword(s):  
Decision Making ◽  
Drug Development ◽  
Development Process ◽  
Surrogate Endpoints ◽  
Pharmacokinetic Data ◽  
Drug Development Process ◽  
High Likelihood ◽  
Molecular Pharmacology ◽  
Toxicity Biomarkers ◽  
The Cost

As the pharmaceutical industry starts developing novel molecules developed based on molecular biology principles and a better understanding of the human genome, it becomes increasingly important to develop early indicators of activity and/or toxicity. Biomarkers are measurements based on molecular pharmacology and/or pathophysiology of the disease being evaluated that may assist with decision-making in various phases of drug development. The utility of biomarkers in the development of drugs is described in this review. Additionally, the utility of pharmacokinetic data in drug development is described. Development of biomarkers may help reduce the cost of drug development by allowing key decisions earlier in the drug development process. Additionally, biomarkers may be used to select patients who have a high likelihood of benefit or they could be used by clinicians to evaluate the potential for efficacy after start of treatment.

Epilogue: New Drugs for Neglected Diseases

2011 ◽  
Vol 20 (2) ◽  
pp. 329-334 ◽  
Author(s):  
THOMAS POGGE ◽  
AIDAN HOLLIS
Keyword(s):  
Research And Development ◽  
Pharmaceutical Research ◽  
New Drugs ◽  
Neglected Diseases ◽  
Innovation Cost ◽  
Adjusted Rate ◽  
Medicine Today ◽  
The Cost ◽  
Year 2000 ◽  
Pharmaceutical Research And Development

In a widely cited 2003 article, DiMasi, Hansen, and Grabowski estimated the cost of pharmaceutical research and development to be $1.1 billion (year 2000 U.S. dollars) per new medicine coming onto the market in 2001. They also estimate that this cost is going up at a real (inflation-adjusted) rate of 7.4% annually. According to these estimates, the innovation cost per new medicine today is about $2.1 billion (year 2000 U.S. dollars) or $2.65 billion (year 2010 U.S. dollars).

scholarly journals n Artificial Intelligence Approach Based on Hybrid CNN-XGB Model to Achieve High Prediction Accuracy through Feature Extraction, Classification and Regression for Enhancing Drug Discovery in Biomedicine

2021 ◽  
Vol 15 ◽  
pp. 190-201
Author(s):  
Mukesh Madanan ◽  
Biju T. Sayed ◽  
Nurul Akhmal Mohd Zulkefli ◽  
Nitha C. Velayudhan
Keyword(s):  
Neural Network ◽  
Drug Discovery ◽  
Cell Line ◽  
Prediction Accuracy ◽  
Response Prediction ◽  
New Drugs ◽  
Computational Time ◽  
Molecular Features ◽  
The Cost ◽  
Drug Efficiency

In the field of biomedicine, drug discovery is the cycle by which new and upcoming medicines are tested and invented to cure ailments. Drug discovery and improvement is an extensive, complex, and exorbitant cycle, settled in with a serious extent of vulnerability that a drug will really be successful or not. Developing new drugs have several challenges to enrich the current field of biomedicine. Among these ultimatums, predicting the reaction of the cell line to the injected or consumed drug is a significant point and this can minimize the cost of drug discovery in sophisticated fashion with a stress on the minimum computational time. Herein, the paper proposes a deep neural network structure as the Convolutional Neural Network (CNN) to detain the gene expression features of the cell line and then use the resulting abstract features as the input data of the XGBoost for drug response prediction. Dataset constituting previously identified molecular features of cancers associated to anti-cancer drugs are used for comparison with existing methods and proposed Hybrid CNNXGB model. The results evidently depicted that the predicted model can attain considerable enhanced performance in the prediction accuracy of drug efficiency.

scholarly journals Improving the Prediction of Clinical Success Using Machine Learning

2021 ◽  
Author(s):  
Bernard Munos ◽  
Jan Niederreiter ◽  
Massimo Riccaboni
Keyword(s):  
Machine Learning ◽  
Historical Data ◽  
Clinical Success ◽  
Pharmaceutical Research ◽  
Machine Learning Algorithms ◽  
New Drugs ◽  
Drug Candidates ◽  
The Cost ◽  
D Investment

AbstractIn pharmaceutical research, assessing drug candidates’ odds of success as they move through clinical research often relies on crude methods based on historical data. However, the rapid progress of machine learning offers a new tool to identify the more promising projects. To evaluate its usefulness, we trained and validated several machine learning algorithms on a large database of projects. Using various project descriptors as input data we were able to predict the clinical success and failure rates of projects with an average balanced accuracy of 83% to 89%, which compares favorably with the 56% to 70% balanced accuracy of the method based on historical data. We also identified the variables that contributed most to trial success and used the algorithm to predict the success (or failure) of assets currently in the industry pipeline. We conclude by discussing how pharmaceutical companies can use such model to improve the quantity and quality of their new drugs, and how the broad adoption of this technology could reduce the industry’s risk profile with important consequences for industry structure, R&D investment, and the cost of innovation

scholarly journals Medicinal Plants Used in Mali for the Treatment of Malaria and Liver Diseases

2016 ◽  
Vol 11 (3) ◽  
pp. 1934578X1601100
Author(s):  
Mahamane Haidara ◽  
Geneviève Bourdy ◽  
Nunziatina De Tommasi ◽  
Alessandra Braca ◽  
Korotoumou Traore ◽  
...  
Keyword(s):  
Medicinal Plants ◽  
Traditional Medicine ◽  
Liver Diseases ◽  
Pharmaceutical Research ◽  
New Drugs ◽  
Argemone Mexicana ◽  
Traditional Medicines ◽  
Combretum Micranthum ◽  
The Cost ◽  
Nauclea Latifolia

Today, ethno-pharmacology is a very important resource in order to discover new therapies for the current diseases. Moreover, another good justification for the ethno-pharmacological approach is to obtain new, effective, less expensive and simple therapies, limiting at the same time the cost of pharmaceutical research. Two major anti-malarial drugs widely used today, i.e. quinine and artemisinin, came respectively from Peruvian and Chinese ancestral treatments reported in the traditional medicines. In this contest, there is an urgent need for the discovery of new drugs, due to the critical epidemiological situation of this disease and to the growth of resistances. In Mali, malaria and liver diseases remain one of the leading public health problems. Many medicinal plants are often used, in local traditional medicine, for the treatment at the same time of malaria and liver diseases, including hepatic syndromes, jaundice, hepatitis and other hepatic disorders. Moreover, in the local language Bamanan, the word “ Sumaya” is used both for malaria and some liver diseases. In addition, we noted that some of the improved traditional phytomedicines produced by the Department of Traditional Medicine are prescribed by modern doctors both for malaria and liver diseases. In this review, pharmacological, toxicological and phytochemical data on Argemone mexicana L. (Papaveraceae), Cochlospermum tinctorium Perr. ex A. Rich (Cochlospermaceae), Combretum micranthum G.Don (Combretaceae), Entada africana Guillet Perr. (Mimosaceae), Erythrina senegalensis A. DC (Fabaceae), Mitragyna inermis (Willd) Kuntze (Rubiaceae), Nauclea latifolia Smith syn. Sarcocephalus latifolius (Smith) Bruce (Rubiaceae), Securidaca longepedunculata Fresen (Polygalaceae), Trichilia emetica Vahl. (Meliaceae), and Vernonia colorata (Willd) Drake (Asteraceae) are reported. Some of the collected data could be used to improve the actual herbal drugs and to propose new phytomedicines for the management of malaria and liver diseases.

scholarly journals Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development

Processes ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 71
Author(s):  
Outi M. H. Salo-Ahen ◽  
Ida Alanko ◽  
Rajendra Bhadane ◽  
Alexandre M. J. J. Bonvin ◽  
Rodrigo Vargas Honorato ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Drug Discovery ◽  
Drug Development ◽  
Development Process ◽  
Md Simulations ◽  
Disordered Proteins ◽  
Drug Development Process ◽  
Formulation Development ◽  
Pharmaceutical Development

Molecular dynamics (MD) simulations have become increasingly useful in the modern drug development process. In this review, we give a broad overview of the current application possibilities of MD in drug discovery and pharmaceutical development. Starting from the target validation step of the drug development process, we give several examples of how MD studies can give important insights into the dynamics and function of identified drug targets such as sirtuins, RAS proteins, or intrinsically disordered proteins. The role of MD in antibody design is also reviewed. In the lead discovery and lead optimization phases, MD facilitates the evaluation of the binding energetics and kinetics of the ligand-receptor interactions, therefore guiding the choice of the best candidate molecules for further development. The importance of considering the biological lipid bilayer environment in the MD simulations of membrane proteins is also discussed, using G-protein coupled receptors and ion channels as well as the drug-metabolizing cytochrome P450 enzymes as relevant examples. Lastly, we discuss the emerging role of MD simulations in facilitating the pharmaceutical formulation development of drugs and candidate drugs. Specifically, we look at how MD can be used in studying the crystalline and amorphous solids, the stability of amorphous drug or drug-polymer formulations, and drug solubility. Moreover, since nanoparticle drug formulations are of great interest in the field of drug delivery research, different applications of nano-particle simulations are also briefly summarized using multiple recent studies as examples. In the future, the role of MD simulations in facilitating the drug development process is likely to grow substantially with the increasing computer power and advancements in the development of force fields and enhanced MD methodologies.

Ethics at Phase 0: Clarifying the Issues

2007 ◽  
Vol 35 (4) ◽  
pp. 727-733 ◽  
Author(s):  
Jonathan Kimmelman
Keyword(s):  
Development Process ◽  
Science Studies ◽  
Critical Path ◽  
Clinical Applications ◽  
New Drugs ◽  
Product Development Process ◽  
Drug Development Process ◽  
The Past ◽  
Phase 0 ◽  
Similar Vein

Many commentators have expressed concern that large investments in biomedical research over the past two decades have not been translated effectively into clinical applications. In its Critical Path Report, the Food and Drug Administration (FDA) characterized the problem as a “technological disconnect between discovery and the product development process,” and documented that the number of investigational new drugs (INDs) submitted to the agency had declined “significantly” since 2000. Along a similar vein, another study found that only five of 101 basic science studies showing significant therapeutic promise were successfully translated into clinical applications.This perceived translational lag is stimulating a shift toward human testing of study interventions earlier in the drug development process. One indication of this trend is a recent guidance encouraging sponsors to pursue human “exploratory” studies before embarking on phase I trials.

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