Loewe additivity

In toxicodynamics and pharmacodynamics, Loewe additivity (or dose additivity) is one of several common reference models used for measuring the effects of drug combinations.[1][2][3]

Definition

Let d 1 {\displaystyle d_{1}} and d 2 {\displaystyle d_{2}} be doses of compounds 1 and 2 producing in combination an effect e {\displaystyle e} . We denote by D e 1 {\displaystyle D_{e1}} and D e 2 {\displaystyle D_{e2}} the doses of compounds 1 and 2 required to produce effect e {\displaystyle e} alone (assuming this conditions uniquely define them, i.e. that the individual dose-response functions are bijective). D e 1 / D e 2 {\displaystyle D_{e1}/D_{e2}} quantifies the potency of compound 1 relatively to that of compound 2.

d 2 D e 1 / D e 2 {\displaystyle d_{2}D_{e1}/D_{e2}} can be interpreted as the dose d 2 {\displaystyle d_{2}} of compound 2 converted into the corresponding dose of compound 1 after accounting for difference in potency.

Loewe additivity is defined as the situation where d 1 + d 2 D e 1 / D e 2 = D e 1 {\displaystyle d_{1}+d_{2}D_{e1}/D_{e2}=D_{e1}} or d 1 / D e 1 + d 2 / D e 2 = 1 {\displaystyle d_{1}/D_{e1}+d_{2}/D_{e2}=1} .

Geometrically, Loewe additivity is the situation where isoboles are segments joining the points ( D e 1 , 0 ) {\displaystyle (D_{e1},0)} and ( 0 , D e 2 ) {\displaystyle (0,D_{e2})} in the domain ( d 1 , d 2 ) {\displaystyle (d_{1},d_{2})} .

If we denote by f 1 ( d 1 ) {\displaystyle f_{1}(d_{1})} , f 2 ( d 2 ) {\displaystyle f_{2}(d_{2})} and f 12 ( d 1 , d 2 ) {\displaystyle f_{12}(d_{1},d_{2})} the dose-response functions of compound 1, compound 2 and of the mixture respectively, then dose additivity holds when

d 1 f 1 1 ( f 12 ( d 1 , d 2 ) ) + d 2 f 2 1 ( f 12 ( d 1 , d 2 ) ) = 1 {\displaystyle {\frac {d_{1}}{f_{1}^{-1}(f_{12}(d_{1},d_{2}))}}+{\frac {d_{2}}{f_{2}^{-1}(f_{12}(d_{1},d_{2}))}}=1}

Testing

The Loewe additivity equation provides a prediction of the dose combination eliciting a given effect. Departure from Loewe additivity can be assessed informally by comparing this prediction to observations. This approach is known in toxicology as the model deviation ratio (MDR).[4]

This approach can be rooted in a more formal statistical method with the derivation of approximate p-values with Monte Carlo simulation, as implemented in the R package MDR.[5][clarification needed]

References

  1. ^ Greco, W.R.; Bravo, G.; Parsons, J. (1995). "The Search for Synergy: A Critical Review from a Response Surface Perspective". Pharmacol. Rev. 47 (2): 331–385. PMID 7568331.
  2. ^ Loewe, S. (1926). "Effect of combinations: mathematical basis of problem". Arch. Exp. Pathol. Pharmakol. 114: 313–326. doi:10.1007/BF01952257. S2CID 19783017.
  3. ^ Tang, J.; Wennerberg, J.K.; Aittokallio, T. (2015). "What Is Synergy? The Saariselkä Agreement Revisited". Frontiers in Pharmacology. 6: 181. doi:10.3389/fphar.2015.00181. PMC 4555011. PMID 26388771.
  4. ^ Belden, J. B.; Gilliom, R.; Lydy, M.J. (2007). "How well can we predict the toxicity of pesticide mixtures to aquatic life?". Integr. Environ. Assess. Manag. 3 (3): 364–72. doi:10.1002/ieam.5630030307. PMID 17695109. S2CID 16438339.
  5. ^ "Github development repository for the R package MDR". GitHub. 2020-01-20.


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