Drug Interaction Screening
Drug Interaction Screening - Related Videos
01:30
Drug toxicity: Drug–Drug Interaction
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2026
Drug–drug interactions can precipitate toxicity through multiple mechanisms. Absorption interactions alter how drugs enter the body, exemplified when ranitidine increases the absorption of basic drugs, while cholestyramine decreases the levels of propranolol. Protein binding interactions occur when drugs share the same binding sites on plasma proteins. Drugs like aspirin and warfarin, when bound in excess, can lead to increased free drug concentrations, enhancing the potential for...
01:25
Pharmacokinetics: Drug–Drug Interactions
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2025
Drug interactions occur when the pharmacological effect of one drug is altered by another substance, either enhancing or diminishing its activity. The drug whose activity is altered is known as the object drug, and the substance causing the alteration is called the agent drug or the precipitant. The net effects of these interactions are mostly undesirable, leading to decreased effectiveness or increased adverse effects. In rare cases, interactions can be beneficial, such as the enhanced...
11:56
Nanomechanics of Drug-target Interactions and Antibacterial Resistance Detection
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Cited by 4 •
2013
Acquired resistance to antibiotics is a major public healthcare problem and is presently ranked by the WHO as one of the greatest threats to human life. Here we describe the use of cantilever technology to quantify antibacterial resistance, critical to the discovery of novel and powerful agents against multidrug resistant bacteria.
11:28
3D Microtissues for Injectable Regenerative Therapy and High-throughput Drug Screening
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Cited by 7 •
2017
This protocol describes the fabrication of elastic 3D macroporous microcryogels by integrating microfabrication with cryogelation technology. Upon loading with cells, 3D microtissues are generated, which can be readily injected in vivo to facilitate regenerative therapy or assembled into arrays for in vitro high-throughput drug screening.
01:29
Drug-Receptor Interactions
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2025
Drug-receptor interaction describes the binding of receptors by drugs, but not all drug-receptor interactions result in activation and tissue response. For instance, the binding of agonists activates the receptor to generate a cellular reaction, while antagonists bind to receptors without causing their activation. Several parameters, such as the drug's affinity for its receptor and its efficacy, which is its ability to activate the receptor, determine the drug's effect on the tissue.
FAQs
Investigators classify an interaction by comparing the response produced by a drug combination with the responses produced by each drug alone. A synergistic result indicates greater activity than expected from the individual treatments, whereas an additive result reflects a combined effect consistent with their separate activities. An antagonistic result shows that the drugs counteract one another.
Testing combinations across concentration ranges shows whether an interaction remains consistent or changes as drug exposure changes. A pairing may produce stronger or weaker effects at different concentrations, so a single tested level could give an incomplete profile. This broader evaluation helps investigators distinguish potentially useful combinations from effects that occur only under limited experimental conditions.
Combination testing can identify pairings that produce stronger tumor-cell killing than either drug alone, including combinations that may overcome treatment resistance. Comparing these responses across experimental conditions helps prioritize treatments with complementary activity. The findings do not by themselves establish clinical effectiveness, but they can indicate which combinations merit additional preclinical investigation.
A typical experiment selects two or more drugs, exposes tumor cells or another defined experimental model to individual drugs and combinations, and tests those treatments across concentration ranges. Investigators then measure the resulting responses and compare combination effects with single-drug effects. This comparison supports classification of the interaction and helps determine whether the pairing warrants further study.
Tumor cells provide a direct model for examining how drug combinations affect cancer-related responses, while other experimental models can extend the evaluation beyond a single cell system. Using a defined model makes treatment conditions and comparisons more consistent. The resulting interaction profile helps researchers decide which combinations should advance in preclinical cancer research.
Results can help prioritize combinations that enhance cancer-cell killing, reduce the dose required for activity, or address treatment resistance. They can also identify counterproductive pairings with antagonistic effects, preventing those combinations from receiving the same development priority. In this way, screening informs preclinical study design and narrows the range of therapies selected for further evaluation.