Molecules

A method for designing and synthesizing a drug compound having a particular property for a desired use, the method comprising:

• defining a set of n achievement objectives (OA1-n), where n is at least one;
• defining a population (PG=0) of at least one molecule;
• selecting an initial population (Pparent) of at least one molecule (I1-Im) from the population (PG=0);
• evaluating, by a computer device, members (I1-Im) of the initial population (Pparent) against at least one of the n achievement objectives (OA1-x), where x is from 1 to n;
• wherein the evaluating the members (I1-Im) of the initial population (Pparent) comprises:
• calculating the parameters of each member (I1-Im) of the initial population f(Pparent) for the at least one achievement objective (OA1-x);
• and
• calculating vector distance (VD) from each member (I1-Im) to the at least one achievement objective (OA1-x);
• wherein the vector distance (VD) between each member (I1-Im) and the at least one achievement objective (OA1-x) is defined as:
• VD
• ⁢
• ⁢
• V
• A
• =
• ∑
• p
• =
• 1
• n
• ⁢
• (
• x
• I
• p
• -
• x
• A
• p
• )
• 2
• ,
• wherein a desired value of each of the achievement objectives (OA1-n) has coordinates (xI1, . . . , xIn), and a calculated value of the corresponding parameter p for each member (I1-Im) of the initial population has coordinates (xA1, . . . , xAn);
• and
• determining whether a stop condition is satisfied;
• (a) upon determining that the stop condition is satisfied, performing a first process including:
• ranking members (I1-Im) of the evaluated initial population (Pparent) according to a shortest vector distance (VD) and optionally Pareto frontier to the set of n achievement objectives (OA1-n), wherein a first ranked member (I1-Im) has a shortest vector distance (VD) to the set of n achievement objectives (OA1-n) compared to any other vector distance (VD) of any other ranked member (I1-Im), and
• identifying a set of z ranked members including at least the first ranked member (I1-Im) of the evaluated initial population (Pparent), where z is 1, 2, 5, 10, 20,50 or 100;
• and
• (b) upon determining that the stop condition is not satisfied, performing a second process including:
• performing a first iteration (G=1) of an evolutionary algorithm to generate and evaluate a new population (PG) of at least one molecule by:
• transforming at least one member of the parent population (Pparent) to generate a transformed population (Ptransformed) of at least one molecule;
• defining a new population (PG) of at least one molecule, the new population (PG) comprising at least one member of the transformed population (Ptransformed);
• optionally evaluating the new population (PG) against at least one achievement objective (OA1-x), and selecting molecules from the evaluated population (PG) by applying a strategy function (S);
• defining a new population (PG+1) of at least one molecule (I1-Im);
• and
• evaluating members (I1-Im) of the new population (PG+1) against the at least one achievement objective (OA1-x);
• wherein the evaluating the new population (PG) comprises performing the calculation of vector distance (VD) to the at least one achievement objective (OA1-x) to identify a set of z ranked members including at least a first ranked member (I1-Im) of the evaluated new population (PG) having a shortest vector distance to the at least one achievement objective (OA1-x);
• and
• selectively synthesizing the drug compound based on any of the members of the identified set of z ranked members (I1-Im) of the evaluated initial population (Pparent) or based on any of the members of the identified set of z ranked members (I1-Im) of the evaluated new population (PG).