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Patent Issued for System and Method of Evaluation of Stochastic Interactions of a Soluble Ligand with a Target Cell Population for Optimization of...

February 24, 2014



Patent Issued for System and Method of Evaluation of Stochastic Interactions of a Soluble Ligand with a Target Cell Population for Optimization of Drug Design and Delivery

By a News Reporter-Staff News Editor at Clinical Trials Week -- From Alexandria, Virginia, NewsRx journalists report that a patent by the inventors Kirnasovsky, Oleg U. (Bene Ataroth, IL); Vainstein, Vladimir (Bene Ataroth, IL); Kogan, Yuri (Bene Ataroth, IL); Agur, Zvia (Ramat Gan, IL), filed on June 9, 2006, was published online on February 11, 2014 (see also Optimata Ltd.).

The patent's assignee for patent number 8650017 is Optimata Ltd. (Ramat Gan, IL).

News editors obtained the following quote from the background information supplied by the inventors: "During last two decades the progress in the molecular biology has led to development of 'the targeted molecular therapy', which consists of macromolecular drugs that specifically interact with a certain target cell population. This interaction is frequently mediated by a specific binding of a ligand (here and further on--any soluble substance used as a part of treatment for certain disease, e.g. drug, prodrug, etc.) to a receptor that is expressed on the cell surface (here and further on we use the term 'receptor' in a broad sense--any macromolecule expressed on the cell surface, which specifically binds the mentioned ligand).

"Pharmacokinetics (PK) and pharmacodynamics (PD) of ligands (both unconjugated ones and their conjugates with chemotherapeutic, enzymatic, radioactive and other agents) are complex and include PK in the blood, the perfusion--and diffusion--limited transport phenomena in the blood-tissue border, binding of ligands to their receptors, and finally their effect on the target cells (cell-mediated ligand-dependent cytotoxicity, a complement activation, an effect induced by the conjugate, a cell signaling cascade induction by an activation of the receptor upon ligand binding, etc). This complexity demands development of computational tools for optimization of drug design, treatment protocol choice and individualization of the treatment.

"Several aspects of this complex process (including the perfusion, the diffusion, the tissue distribution, the conjugate efficacy) have been analyzed in the case of monoclonal antibodies by mathematical models (Jackson et al., Friedrich et al., Baxter et al.). This analysis can be very important for an evaluation of applicability of a specific monoclonal antibody (with or without a conjugate) to a certain disease prior to performing time--and resource--consuming clinical trials. However, in all cited models, description of the process of binding of a ligand (a monoclonal antibody) to their target is based solely on two values--the average number of receptors (antigens) per cell and the dissociation constant (the ratio of dissociation and the association rates between a specific monoclonal antibody and its antigen). These models do not take into account the fact that binding and dissociation of a ligand are stochastic processes, and consequently, the number of the bound antibodies can vary considerably between individual cells even if they are identical with respect to the antigen kinetics. Therefore drug efficacy can be easily over- or underestimated, rendering exact quantitative predictions of the in vivo effect highly unreliable."

As a supplement to the background information on this patent, NewsRx correspondents also obtained the inventors' summary information for this patent: "The disclosed teachings are aimed at overcoming some of the above noted problems. The disclosed teachings specifically provide analysis of interaction of a soluble ligand with population(s) of target cells. The disclosed techniques are very general, since they are based on a small number of biologically justified assumptions. The techniques can be implemented for different types of normal and pathological cell populations and various ligand-receptor pairs.

"To realize the advantages there is provided a computer system for recommending an optimal treatment protocol comprising a model of biological processes related to a disease; a treatment protocol generator for generating a plurality of treatment protocols for treating a disease using drugs; and a selector adapted to select an optimal treatment protocol from said plurality of treatment protocols based on the model. The model further comprises a pharmacokinetics macro module adapted to analyze interactions between a ligand and a population of target cells at a tissue level. The model further comprises a pharmacokinetics micro module adapted to analyze interactions between the ligand and a cell at an individual cell level. The pharmacokinetics micro module is adapted to model behavior of the ligand and receptors related to single cell level of ligand-cell interactions, as a stochastic process.

"In another specific enhancement, the model further comprises a pharmacodynamics module that is adapted to model actual effects of ligands on the population of target cells using pharmacokinetics modules' outcome.

"More specifically, the pharmacokinetics micro module is operable to compute a distribution of cells according to a number of bound receptors and a number of free receptors in a cell.

"More specifically, the distribution of cells is provided to the pharmacodynamics module.

"In another specific enhancement, the stochastic process is a Markov chain.

"In another specific enhancement the ligand is a monoclonal antibody.

"In another specific enhancement, the receptor is an antigen on the cell surface of said target cells.

"In another specific enhancement, the target cell population is cancerous.

"In another specific enhancement, the pharmacokinetics macro module is a system of differential equations, each of said differential equation describing behavior of a separate parameter.

"More specifically, the Markov chain is countable and continuous in time.

"More specifically, the differential equations include at least one selected from an equation denoting molar concentrations of free antibodies as a function of time, equation denoting molar concentrations of free antigens as a function of time, equation denoting molar concentrations of bound antigens as a function of time, equation denoting molar concentrations of internalized conjugates.

"More specifically, a base set of the Markov chain is chosen to form an infinite grid of states wherein each of said states is a cell that includes a set of free antigens and a set of bound antigens.

"More specifically, the model is adapted to consider at least one of the next moves selected from: a free antigen binding with an antibody; a free antigen undergoing internalizations, a bound antigen undergoing internalization, a bound antigen disassociating and a new free antigen being produced. Each of the next moves proceeds with a predetermined probability density.

"In another specific enhancement, the pharmacokinetics macro module is assumed to arrive at steady state prior to implementing the micro module.

"In another specific enhancement, the pharmacodynamics module includes an effector function that computes ligand effects.

"In another specific enhancement, the system further comprises a model modifier operable to modify the model based on parameters specific to an individual.

"Another aspect of the disclosed teachings is a computer-implemented method for recommending an optimal treatment protocol for treating a disease comprising modeling biological processes related to the disease. A plurality of treatment protocols are enumerated for treating the disease using drugs. An optimal treatment protocol is selected from said plurality of treatment protocols based on the modeling. The optimal treatment is recommended to the patient. The modeling further includes analyzing interactions between a ligand and a population of target cells at a tissue level using a pharmacokinetics macro module. The modeling further includes analyzing interactions between the ligand and a cell at an individual cell level using a pharmacokinetics micro module. The pharmacokinetics micro module models behavior of the ligand and receptors related to single cell level of ligand-cell interactions, as a stochastic process."

For additional information on this patent, see: Kirnasovsky, Oleg U.; Vainstein, Vladimir; Kogan, Yuri; Agur, Zvia. System and Method of Evaluation of Stochastic Interactions of a Soluble Ligand with a Target Cell Population for Optimization of Drug Design and Delivery. U.S. Patent Number 8650017, filed June 9, 2006, and published online on February 11, 2014. Patent URL: http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&p=22&u=%2Fnetahtml%2FPTO%2Fsearch-bool.html&r=1082&f=G&l=50&co1=AND&d=PTXT&s1=20140211.PD.&OS=ISD/20140211&RS=ISD/20140211

Keywords for this news article include: Antibodies, Treatment, Immunology, Optimata Ltd., Blood Proteins, Immunoglobulins, Clinical Trials and Studies.

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Source: Clinical Trials Week


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