Rank-order approach

Obach, R.S., Walsky, R.L, Venkatakrishnan, K., Houston, J.B. and Tremaine, L.M. (2005) vitro cytochrome P450 inhibition data and the prediction of drug-drug interactions qualitative relationships, quantitative predictions, and the rank-order approach. Clinical Pharmacology and Therapeutics, 78, 582-592. 

Use of in vitro data to prospectively predict DDIs is diflhcult and some have proposed a relatively simple rank-order approach (Obach et ah, 2005). In this instance, a NCE is evaluated as an inhibitor of different CYP forms in vitro. Standardized ineubation conditions are employed, so that the ICsqS or for each CYP form are ranked in order of increasing potency. The CYP form with the lowest IC50 or K is evaluated first in the clinic. For example, the inhibition is greatest with CYP3A4, and then a midazolam clinical DDI study is initiated first. Other CYPs are followed up with suitable probe drugs as needed (Table 5.4). 

According to the nature of the activity data, QSAR studies can be divided into continuous (activities, i.e., response variable, takes many different values from within some interval), category (activities are represented by ranks or ordinal numbers), and classification (activities are different types of biological properties which cannot be rank ordered) approaches. 

Significance of risk contribution may be done by ordering the risk contributors from most-to-least (rank order), but because of the arbitrariness of variation of the variables, this may be meaningless A more systematic approach is to calculate the fractional change in risk or reliability for a fractional change in a variable. 

A number of approaches to predict ionization based on structure have been published (for a review, see [53]) and some of these are commercially available. Predictions tend to be good for structures with already known and measured functional groups. However, predictions can be poor for new innovative structures. Nevertheless, pfCa predictions can still be used to drive a project in the desired direction and the rank order of the compounds is often correct. More recently training algorithms have also become available which use in-house data to improve the predictions. This is obviously the way forward. 

In summary, computational quantum mechanics has reached such a state that its use in chemical kinetics is possible. However, since these methods still are at various stages of development, their routine and direct use without carefully evaluating the reasonableness of predictions must be avoided. Since ab initio methods presently are far too expensive from the computational point of view, and still require the application of empirical corrections, semiempirical quantum chemical methods represent the most accessible option in chemical reaction engineering today. One productive approach is to use semiempirical methods to build systematically the necessary thermochemical and kinetic-parameter data bases for mechanism development. Following this, the mechanism would be subjected to sensitivity and reaction path analyses for the determination of the rank-order of importance of reactions. Important reactions and species can then be studied with greatest scrutiny using rigorous ab initio calculations, as well as by experiments. 

Equilibrium solubility This approach is considered a first attempt to characterize the true thermodynamic solubility of the compound. It is used to rank-order compounds and to extract a structure-solubility relationship within the chemical series. In this assay, compounds are usually equilibrated for 24 h before analysis. One can start from powder, but this is a quite labor-intensive step. In most cases one starts from DMSO stock solutions (usually 10 mM) because it is much more efficient from a compound logistics viewpoint. The solvent is then usually removed and the compound is dried before addition of the buffer medium [15, 16]. 

This approach makes the assumption that any effects on V ax are independent of substrate, i.e. the rank order of rates of metabolism is the same for a particular cDNA-expressed enzyme and the same enzyme present in human tissue preparations, and any factor which affects V ax for one substrate also does so equally for other substrates. The validity of this assumption has not been rigorously tested but for most enzymes an appropriate set of test compounds is available. 

Another consideration is the rank order of rates of metabolism for different substrates for the same enzyme. At present there are insufficient data to determine if there are differences in rank orders of rates of metabolism for the cDNA-expressed enzymes from different systems relative to human liver enzymes. If rank orders of rates of metabolism for cDNA-expressed enzymes are indeed different from human liver microsomes, it will be nearly impossible to determine the principal P450 using the RAF approach. 

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