A New Quantitative Index for Optimization of Drug Doses in the Treatment of AIDS.

Marco Antonio Leonel Caetano; Takashi Yoneyama. UNESP – Rio ClaroBrazil; ITA –S.J.Campos  (Brazil).

Background: A new quantitative index is proposed to reflect the compromise between the therapeutic and side effects during treatment of AIDS using drugs. This type of index is useful in computer programs for numerical simulation and optimization of different types of drug administration schemes. Material and Methods: A sample of 43 patients was selected from a database with about 5.000 records at Centro de Referencia e Tratamento em DST/AIDS in São Paulo city, Brazil. Those 43 patients satisfied the eligibility conditions specified a priori. The collected data included the administered drug doses, CD4+ T cell counts and viral loads, together with clinical conditions as reported by medical doctors. Results: The proposed performance index tries to quantify the side-effects that are related to the drug doses while also taking into account the clinical conditions as reflected by the values of CD4+T cell counts and viral load.

The heuristic interpretation of the proposed cost functional is that the first two terms in the  summation represent the side-effects due to m1 and m2, respectively. Here m1 is the reverse transcriptase inhibitor and m2 is the protease inhibitor. Analogously to the therapeutic effect, the side-effect is also assumed to present a saturation and, hence, modelled by a negative exponential. The coefficients a1, a2,  f1 and f2 are constants. The third and the fourth terms, involving CD4+T cell count and the viral load,  represent the therapeutic-effects. These terms   are small (favourable) when CD4+T cell count is large (elevated number of CD4+T cells) and the viral load is small (favourable). The weights g1 and g2 are constants. The constants a1, a2,  f1, f2, g1 and g2 were ajusted to reflect the actual clinical data

Conclusion: This work proposed a new quantitative index that conforms to the trends shown by the actual clinical data of sero positive patients. This index can be used to optimize the drug administration schemes via numerical methods. Moreover, by numerical simulations, adequate clinical results were achieved in terms of improved compromise between the side effects, reduction of the viral load and increase in the CD4+ T cell counts.