Drug Optimization
Drug Optimization - Related Videos
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Establishment and Optimization of a High Throughput Setup to Study Staphylococcus epidermidis and Mycobacterium marinum Infection as a Model for Drug Discovery
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Cited by 25 •
2014
This video article describes the high throughput pipeline that has been successfully established to infect and analyze large numbers of zebrafish embryos providing a new powerful tool for compound testing and drug discovery using a whole animal vertebrate organism.
03:37
Optimal Foraging - Concepts
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2019
Optimal Foraging Organisms must acquire and use resources in their environment to survive. While food is one of the primary resources organisms must search for, individuals also need to seek habitats, shelter, and mates. This process of searching for resources is known as foraging, which involves a series of costs and benefits. More specifically, acquiring a resource provides the organism with a benefit, however, searching and capturing the resource requires expenditure of time and energy.
00:48
Optimal Foraging
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2019
How animals obtain and eat their food is called foraging behavior. Foraging can include searching for plants and hunting for prey and depends on the species and environment. Optimal foraging theory states that natural selection favors foraging strategies that balance the benefits of a particular food, such as energy and nutrients, with the costs of obtaining it, such as energy expenditure and the risk of predation. Optimal foraging maximizes benefits while minimizing costs. For the Crows
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Optimal Foraging - Student Protocol
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2019
Simulating Foraging with Artificial Habitats and Prey ExpandNOTE: The foragers will hunt for prey represented by pinto beans in four buckets of rice with varying prey densities. Without knowing what these densities are, foragers must obtain as many prey items as possible in as little time as possible. HYPOTHESES: In this experiment, the experimental hypothesis could be that foragers will catch the most prey in the higher prey density bucket and also spend the most time foraging there. The...
05:10
Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
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Cited by 4 •
2016
Here we describe a protocol using the web-based drug repurposing hypothesis generation tool: "RE:fine Drugs." This protocol can be modified to a user's preferences at the level of the query type (gene, drug or disease) and/or the range of available advanced options.
FAQs
Exposure provides a link between the amount of drug reaching the body and the response observed during treatment. Drug optimization examines this relationship alongside adverse effects to determine whether a candidate produces sufficient therapeutic benefit without unacceptable risk. This analysis can inform dose selection and help explain why different exposure levels may lead to different clinical outcomes.
Pharmacokinetic evidence addresses drug exposure, while pharmacodynamic evidence addresses the resulting biological or clinical response. Considering both helps researchers evaluate how dosing influences what the body experiences and how the patient responds. Their integration supports more informed dose selection and treatment schedules than relying on effectiveness or exposure measurements alone.
Treatment schedules determine how dosing is organized over time, which can influence exposure, response, and adverse effects. Patient stratification groups patients according to relevant differences observed in clinical evidence, allowing researchers to assess whether particular groups respond differently. Together, these approaches can support more consistent outcomes and contribute to personalized treatment strategies.
Optimization draws on pharmacology, pharmacokinetics, pharmacodynamics, dosing information, formulation considerations, and clinical-trial findings. Each evidence stream contributes a different view of the candidate's likely performance, from drug properties and exposure to response and adverse effects. Reviewing them together helps development teams make more efficient decisions about clinical suitability and further testing.
Formulation and dosing help determine whether a therapeutic candidate can be used in a practical and clinically appropriate way. Researchers consider them with evidence on exposure, response, and adverse effects rather than treating effectiveness as the only criterion. This integrated assessment can guide choices about dose selection and treatment schedules before broader clinical use.
Combination strategies become an optimization consideration when clinical evidence indicates that using treatments together may improve therapeutic benefit or help balance risk. Researchers can evaluate combinations alongside dosing, exposure, response, and adverse effects to identify a suitable approach. These analyses may support more effective development decisions and help tailor treatment strategies to clinical needs.