US2015370962A1PendingUtilityA1
Pharmaceutical platform technology for the development of natural products
Est. expiryMar 30, 2027(~0.7 yrs left)· nominal 20-yr term from priority
G16B 35/00G16C 20/60A61K 36/48G16C 20/30G06F 18/211C40B 30/02G01N 33/5038G06F 19/16G06F 19/12G06F 19/704G01N 33/483G16B 5/00G16C 20/64
52
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Claims
Abstract
The present invention provides a set of in vitro and in silico methodologies for predicting in vivo pharmacokinetics and pharmacodynamics of multiple components; the methodologies comprise mathematical models for solving multiple unknowns which are linearly independent and/or interacting with each other. The present invention can be applied to develop phytomedicines which contain multiple active ingredients without prior identification, isolation and purification of these components.
Claims
exact text as granted — not AI-modified1 - 22 . (canceled)
23 . A method of preparing a composition comprising multiple components for drug formulations, wherein the identities of or interactions among the components are not known a priori, the method comprises the steps of:
a) preparing multiple samples of a mixture, said mixture comprises the same multiple components at different concentrations, wherein the identities of or interactions among the components are not known a priori; b) using in vitro assays or in silico methods to obtain parameters describing the rate of elimination of said components and their active metabolites in a plurality of mammalian tissue systems; c) using in vitro assays or in silico methods to obtain parameters describing distribution of said components and their active metabolites in a plurality of mammalian tissue systems; d) obtaining pharmacodynamic parameters describing the response of said samples of mixture; e) performing Subset-Selection Principal Component Analysis to reduce dimensionality of the parameters from (b) to (d), thereby generating parameters for active components in the mixture; f) inputting the parameters for active components from (e) into a first computer-based modeling system to estimate optimal weights of the active components, said modeling system comprises
r≈ r +Σ i w i ( d i − d i )+Σ i w′ i ( d i − d i ) 2 +Σ i,j w i,j ( d i − d i )( d j − d j )
min
w
i
,
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i
′
,
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i
,
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{
r
-
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wherein r is linearized response, r is average linearized response; w i is weight of the i th component, w′ i is weight of the non-linear self-interaction behavior of the i th component, d i is the dose of the i th component, d i and d j are average doses of the i th and j th component, and w i,j is the weight of the interacting pair,
min
w
i
,
w
i
′
,
w
i
,
j
is a minimization procedure to minimize the difference between r and said first modeling system by varying w i , w′ i , w i,j ,
wherein said first modeling system generates outputs comprising (i) optimal weights α i and β i,j , which are optimal values of w i and w′ j and w i,j obtained from said minimization procedure, and (ii) total dose of the components D, which is defined as Σ i=1 n d i ;
g) inputting the optimal weights, α i and β i,j , from (f) into a second computer-based modeling system that comprises
A
=
α
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+
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+
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wherein, A is estimated response generated by said active components per total dose, α 0 is an average linearized response per total dose, x i and x j are defined as d′ i /D and d′ 1 /D respectively, which are fractions of said total dose D contributed by the i th and j th component respectively, and wherein D=Σ i=1 n d′ i ,
max
x
is a maximization procedure achieved by varying x i , ∀ i is for all i values,
wherein said second modeling system generates outputs comprising dosages of active components that generate maximal response; and
h) using dosages of active components that generate the maximal response from (g) to prepare a composition comprising multiple components, wherein the dosages for said multiple components are obtained from said dosages of active components that generate the maximal response.
24 . The method of claim 23 , wherein the pharmacodynamic parameters describing the response of an individual component are determined through receptor binding assays, enzymatic assays, biochemical response assays, or assays with isolated tissues or organs.
25 . The method of claim 23 , wherein said outputs of the first and second computer-based modeling systems comprise pharmacokinetic concentration-time profiles and response-time profiles for the components, or comprise pharmacodynamic descriptions on the synergism or inhibition among the components.
26 . The method of claim 23 , wherein the mammalian tissue systems are selected from the group consisting of gastrointestinal tract, liver, kidney, blood, mammary gland, uterus, prostate, brain, and bone.
27 . The method of claim 23 , wherein the rate of elimination comprises one or more parameters selected from the group consisting of rate of metabolism, rate of absorption, and rate of degradation.
28 . The method of claim 27 , wherein the rate of absorption is determined by rate of permeability measured using cultured cells or intestinal tissues.
29 . The method of claim 26 , wherein determining the rate of elimination in gastrointestinal tract comprises assays using artificial gastric or intestinal juice, intestinal flora or intestinal microsomes.
30 . The method of claim 23 , wherein the mixture is from botanical or animal sources.Cited by (0)
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