DDI-Explorer Search Modalities

Unlike many information sources, DDI-Explorer offers more one simple search modality for potential DDIs of a combination of administered drugs. These could be described as follows:

Reported IAs Matrix (one-to-one search)

These represents IAs reported in the scientific literature on single drug–to–single drug basis. This type of information may not be readily accessible in other databases and constitutes a prime cause for the occurrence of preventable medications errors with serious consequences.

Extended Search Matrix (one-to-many or many-to-many search)

Close to 30% of IAs information provided in the clinical literature pertains to interactions between single drugs with a class or group of drug substances or even between groups of drugs. Such IAs reports are often dynamic in nature and imply a significant level of generalization. Reporting in this fashion is:

  1. Considered the main cause of inconsistent reporting by reputable drug information sources and
  2. The prime concern of clinical practioners is to identify IAs between single drugs substances.

Access to relevant interaction information is either cumbersome or not available. In this regard, DDI-Explorer offers a radical solution to this serious shortcoming by virtue of its unique ability to access IA information that is reported for single drugs under their corresponding classes or groups of drug substances through its extended search options.

Induced Drugs Effects Matrix

A definition for Induced Effects (“IEs”) caused by drugs differs slightly from drugs side effects because their presence may be manifested by, or may lead to, some of the known drugs SEs. For example, drugs causing hypo- or hyperkalaemia or QT-interval prolongation (QT-IP) may cause abnormal heart function, albeit they are not side effects per se. The IEs are additive by their very nature. This implies that if one or more than one prescribed drugs have the same IE, the potential for causing SEs will be greater.

IEs are usually reported within the context of DDIs. However, the approach adopted in DDI-Explorer for reporting IEs in a matrix format offers users the opportunity to instantly recognise their presence, irrespective of whether such presence is in one or more than one drug. Occasionally, the presence of hypo-kalaemia or hypo-magnesemia, negative inotropes and bradycardia causing medication may worsen the QT-IP inducers. Such situations are readily and uniquely recognized by DDI-Explorer.

It is rather interesting to note that only 20 QT-IP cases were reported in the latest edition of the BNF. These were mostly provided as undefined members of classes and/or groups of drugs which render such provision of information rather uninformative. Notwithstanding, the FDA documents 215 such cases with due clinical significance rating.

Bradycardia causing medication poses an equivalent threat to patients with cardiac disease similar to that of QT-interval prolongators. Such medications are often poorly reported by many data bases. An example of such poor reported for Lumacaftor with other drugs having such induced effect is provided in Annex V . While 8 interactions are reported by DrugBank and another 6 cases are provided by Lexi-Comp database together with a generalized statement indicating its interactions with bradycardia inducing agents. However, the number of drugs with such effects amount to about 150 drugs that are scattered amongst different information sources.

Kinetic Interactions

Hepatic enzymes and transporters (HET) are protein configurations that affect the duration or stay of drugs in the body and its transportation at both cellular and organ levels. HET are responsible for the transport and elimination of more than 75% of drugs, their role is recognized and extensively documented by international regulatory authorities.

In order to appreciate the HET-IAs, one must recall that drugs may be SUBSTRATES for specific enzyme(s) that cause it elimination from the body. These very drugs may also INDUCE or INHIBIT other enzymes which results in altering their ability to eliminate their SUBSTRATES.

The effects of drugs on enzymes is, by definition, a kinetic effect and is manifested by decreasing or increasing drugs levels in the body which may lead to alteration in their therapeutic or side effects.

Clinical significance rating of this type of IAs is very well documented by different regulatory authorities such as the FDA or EMEA. In some instance the concurrent use of specific drugs may cause more than a 5-fold increase of another drug effect which may result in serious consequences especially for drugs with narrow therapeutic windows.

The HET matrix has multiple functions which could be outlined as follows:

  1. 1. Offers substantiation to result of empirical clinical findings;
  2. Allows clinical practioners to instantaneously predict likely IAs for drugs that have not been subject to such clinical research, and
  3. Offers a unique opportunity to identify drugs that induce or inhibit its own metabolism, a phenomenon known in the scientific literature as AUTO-INDUCTION or AUTO-INHIBITION. While auto-induction is widely acknowledged for certain drugs, auto-inhibition is rarely acknowledged or reported in the literature. Accordingly, the HET matrix offers a novel and unique system for the attainment of more in-depth understanding of drugs kinetics and/or their therapeutic effect(s).

Dynamic Interactions Matrix

This matrix marks the intersecting cell in case of administering to drugs that act on the same target. As yet, no rating or interpretation is provided by the system. The clinical significance and/or interpretation of such interaction are left to the judgement of experienced providers of healthcare.

Dynamic Interactions occur at the target/site of action. The correct identification of likely target(s) has become a regulatory requirement for drug substances prior to their approval for human use. Such information has provided basis for likely bio-interaction between concomitantly administered drugs which would in turn prove crucial for healthcare professionals. In addition, it would provide insight into the underlying causes for an interaction, and also predicts interactions that are not reported in the clinical literature.

With the availability of more information pertaining to targets, it is envisaged that future versions of DDI-Explorer would offer alternative combination of prescribed drugs having lower risk factor or less adverse effects.

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