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Drug Discovery: Overview

Drug Discovery: Overview

Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...

Preclinical Development: Overview

Preclinical Development: Overview

Preclinical development consists of a series of tests that ensure the safety and efficacy of a new therapeutic compound before it is tested in humans. There are four main phases to this process. First, safety pharmacology tests are conducted to ensure the drug does not produce any acutely harmful effects. These tests examine parameters such as bronchoconstriction, cardiac dysrhythmias, blood pressure changes, and ataxia. Next, preliminary toxicological testing is performed to determine the...

Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions

Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions

PK–PD modeling has significantly influenced FDA regulatory decisions, particularly drug approval, dosage optimization, and labeling. These models integrate pharmacokinetics (PK) and pharmacodynamics (PD) to predict drug behavior and effects, aiding in optimizing dosing regimens and enhancing the probability of clinical trial success.One notable example is Nesiritide (Natrecor®), a recombinant human brain natriuretic peptide for treating acute decompensated congestive heart failure (CHF).

Pharmacogenomics: Identification of New Drug Targets

Pharmacogenomics: Identification of New Drug Targets

Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...

Structure-Activity Relationships and Drug Design

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Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
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Clinical Trials: Overview

Clinical Trials: Overview

Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...

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Related Experiment Video

Updated: May 12, 2026

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Published on: December 11, 2016

Net present value approaches for drug discovery.

Andreas M Svennebring¹, Jarl Es Wikberg

¹Department of Pharmaceutical Biosciences, Division of Pharmaceutical Bioinformatics, Biomedical Centre, Uppsala University, Box 591, SE751 24 Uppsala, Sweden.

|April 16, 2013

Summary

This summary is machine-generated.

This study introduces flexible risk-adjusted net present value (rNPV) calculations for drug discovery. It improves financial modeling by considering variable probabilities and timelines for clinical development initiation.

Keywords:

Biotechnology Drug development Drug discovery Investment under uncertainty Life science NPV Risk-adjusted net present value rNPV

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Last Updated: May 12, 2026

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

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Published on: December 11, 2016

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery

Published on: May 16, 2021

Area of Science:

Pharmaceutical Sciences
Financial Modeling
Drug Discovery

Background:

Traditional risk-adjusted net present value (rNPV) models often use rigid assumptions for drug discovery projects.
Accurate financial valuation is crucial for R&D investment decisions in the pharmaceutical industry.

Purpose of the Study:

To propose three novel approaches for calculating rNPV in drug discovery.
To enhance financial modeling by incorporating flexible probabilities and timelines for clinical development.

Main Methods:

Developed three distinct methodologies for rNPV calculation.
Modeled rNPV based on a probability-weighted average of post-discovery cash flows.
Assumed flexible probabilities for identifying suitable drug candidates and variable timelines for clinical development initiation.

Main Results:

The proposed methods allow for more adaptable rNPV calculations compared to previous models.
The study provides a framework for integrating variable success probabilities and development start times into financial assessments.
Practical guidance is offered on setting probability rates, especially at project initiation and termination phases.

Conclusions:

The suggested rNPV approaches offer a more realistic financial assessment of drug discovery projects.
Flexible modeling enhances the strategic decision-making process for pharmaceutical R&D investments.
Accurate probability estimation is key for effective financial risk management in drug development.