How can we weigh the efficacy and side-effects of a drug?
Image credit: Photo by Anna Shvets from Pexels
Computational molecular docking can be a useful technique
- Prediction of Side Effects Using Comprehensive Similarity Measures
- A Novel Triple Matrix Factorization Method for Detecting Drug-Side Effect Association Based on Kernel Target Alignment
- Prediction of Drug Side Effects with a Refined Negative Sample Selection Strategy
The problems "behind the scenes"
- Side effects presented as a minor problem compared to the benefit of a drug
How to know which side-effect is valid? Solution: "Reporter" in every drug
- incorrect dosage
- taking two drugs with known interactions simultaneously
- other off-label use
How can we be completely sure when we attribute a side effect to a drug?
Measuring side effects objectively - PAIN
- the variability of assessment due to the patient/assessor´s psychological and physiological state (pain catastrophizing as an extreme example),
- the questionnaire text can make your pain assessment biased, and incomplete due to the assessor´s predispositions and points of interest and
- the impossibility to measure pain in patients with general anesthesia or with cognitive disorders
Solution - Neuroimaging + AI
The expected final result
The possible application - preclinical testing of drug side effects
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Side Effects are Extremely Complex and Patient-Dependent
- Genetic background: Particular variations of cell receptors can interact differently with certain drugs: This can mean weaker/stronger as well as shorter/longer interactions, or new interactions that were not expected.
- Metabolization of drugs: Is based on processes that can themselves depend on the combination of several factors like activity of different liver enzymes, efficiency of import in different tissues or even unrelated pathological states of organs like the liver.
- Incorrect dosing: Doses for a lot of drugs are based in body weight and severity of symptoms which are not very scientifically precise measurements and do not take into consideration the patient's own biodistribution.
- The status of the body: especially the immune system and the microbiota can be severely affected by drugs if they are already subclinically altered. Similarly, damaged liver and kidney can present reduced processing and secretion of drugs leading to accumulation of the drug or toxic metabolites.
- Unexpected and unexplainable effects: these are very rare but normally severe reactions.
- Type A reactions are usually dose dependent and predictable, and are often recognised before a drug is marketed. Type A reactions are readily reversible by reducing the drug dose or withdrawing the drug. Many commonly documented ADRs are type A reactions. Type A reactions can result from the primary pharmacology of the drug, representing an exaggeration of the drug’s therapeutic actions.
- Type B reactions are unrelated to the known pharmacological actions of a drug and account for approximately 20% of all ADRs . Type B reactions are less common than type A reactions, but they are often serious and associated with high mortality. Type B reactions are often caused by immunological and pharmacogenetic mechanisms (genetically determined variability in response to drugs). Immunological reactions, such as anaphylaxis in response to penicillin, are classed as type B reactions
- Type C reactions, or continuing reactions, persist for a relatively long period of time, for example osteonecrosis of the jaw with the use of bisphosphonates
- Type D, or delayed reactions, appear sometime after the use of a medicine. The timing of type D reactions can make them difficult to detect. For example, lomustine, which is used to treat certain cancers, can cause leucopenia (a reduction in the number of white blood cells) up to 6 weeks after treatment starts
- Type E, or end of use, reactions are linked to the withdrawal of a medicine. For example, the withdrawal symptoms associated with the discontinuation of benzodiazepines for the treatment of anxiety can be prolonged and difficult.
Kaufman G. Adverse drug reactions: classification, susceptibility and reporting. Nurs Stand. 2016 Aug 10;30(50):53-63. doi: 10.7748/ns.2016.e10214. PMID: 27507394.
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