TW201636615A - Method of release testing - Google Patents

Abstract

Methods of measuring systemic release of active drug from a nanoparticle, and their use, for example in assessing bioequivalence are described.

Description

Release test method

The present invention relates to a method of release testing.

It has long been recognized that it is beneficial to differentially deliver certain drugs to a patient (e.g., more preferentially assigned to a particular tissue or cell type or to a particular diseased tissue than to normal tissue) or to control drug release.

For example, a therapy that includes an active agent that is preferentially assigned to a particular diseased tissue more than normal tissue can increase exposure of the drug in those tissues beyond other parts of the body. This is especially important when treating conditions such as cancer where it is desirable to deliver a cytotoxic dose of the drug to the cancer cells without killing surrounding non-cancerous tissue. Effective drug distribution can reduce undesirable and sometimes life-threatening side effects that are common in anticancer agents. In addition, such therapies can allow drugs to reach certain tissues that they would otherwise not reach.

It would also be advantageous to provide a controlled release therapy of the active ingredient.

One way to achieve targeted tissue distribution and controlled release may be by formulating the active ingredient into a nanoparticle formulation, although the differential distribution and controlled release, the route of administration, and the specific contribution of any particular formulation are different in different tumors. Types can vary.

Cancer (and other hyperproliferative diseases) are characterized by uncontrolled cell proliferation. The loss of normal regulation of cell proliferation is often manifested by genetic damage to cellular pathways that progress through cell cycle control.

In eukaryotes, the ordered cascade of protein phosphorylation is thought to control the cell cycle. Several families of protein kinases that play a key role in this cascade have now been identified. The activity of many of these kinases is increased in human tumors when compared to normal tissues. This can occur by increasing the level of protein expression (eg, due to gene amplification), or by altering the expression of the co-promoter or inhibitory protein.

Aurora kinases (Aurora-A, Aurora-B, and Aurora-C) encode a serine-threonine protein kinase that regulates cell cycle (summarized in Adams et al., 2001, Trends in Cell Biology). ).11(2): 49-54). These show peaks in G2 and mitosis and peaks in kinase activity and have long been implicated in the role of human aurora kinase in cancer.

The Aurora kinase inhibitor is called AZD1152 (2-(ethyl(3-((4-((3-fluorophenyl))amino))))))) -pyrazol-3-yl)amino)quinazolin-7-yl)oxy)propyl)amino)ethyldihydrophosphate), as shown in the following figure, first disclosed in International Patent Application WO 2004 /058781 (Example 39) and has been studied by AstraZeneca as a potential treatment for different cancers.

AZD1152 is known to be metabolized in vivo to be called AZD1152 hqpa(2-(3-((7-(3-(ethyl(2-hydroxyethyl))amino)propoxy)quinazolin-4-yl) A compound of amino)-1H-pyrazol-5-yl)-N-(3-fluorophenyl)acetamide, which is also disclosed in WO 2004/058781. In fact, AZD1152 hqpa is largely It is the part that exerts the biological effect when AZD1152 itself is given.

Our PCT application PCT/GB2014/052787 (Publication No. WO 2015/036792) describes a nanoparticle formulation of AZD1152 hqpa.

The therapeutic nanoparticle described in this PCT application comprises from about 50 to about 99.75 wt% of a diblock poly(lactic)-poly(ethylene) glycol copolymer or a diblock poly(lactic acid-glycolic acid copolymer). - a poly(ethyl) glycol copolymer, wherein the therapeutic nanoparticle comprises from about 10 to about 30% by weight of poly(ethylene) glycol, and from about 0.2 to about 30% by weight of AZD1152 hqpa or a pharmaceutical thereof Acceptable salts, especially AZD1152 hqpa. Poly(lactic)-poly(ethylene) glycol copolymers having a poly(lactic acid) having a number average molecular weight of from about 15 kDa to about 20 kDa and a poly(ethylene) glycol having a number average molecular weight of from about 4 kDa to about 6 kDa are described, For example, a poly(lactic)-poly(ethylene) glycol copolymer having a poly(lactic acid) having a number average molecular weight of about 16 kDa and a poly(ethyl) glycol having a number average molecular weight of about 5 kDa is exemplified.

The nanoparticles exemplified in the PCT application also include a substantially hydrophobic acid in which the acid can form a hydrophobic ion pair with AZD1152 hqpa. The exemplified formulations describe a number of suitable hydrophobic acids including deoxycholic acid, cholic acid, dioctyl sulfosuccinic acid (i.e., docusate acid), oleic acid, and pamoic acid. .

During the development of such therapeutic nanoparticle as a potential new drug, it is important to understand how the active ingredient is released from the nanoparticle over time, ie its "release profile". Moreover, in general, one of the requirements for demonstrating that one formulation comprising such nanoparticles is bioequivalent to another such formulation demonstrates that both formulations have the same in vivo release profile. This can be measured as part of an in vivo bioequivalence study the amount.

In the case of nanoparticle formulations, it is difficult to accurately characterize the release profile by directly measuring the released drug.

One of the methods to be used is to provide drug-loaded nanoparticles to the subject, and then, after a period of time has elapsed, attempt to measure the concentration of the "free" drug in the sample from the subject.

An alternative method is to measure the total amount of drug-loaded nanoparticle initially provided to the subject, and then, after a set time in which the drug can be released from the nanoparticle into the subject, is measured in the subject The amount of encapsulated drug that remains circulating in the bloodstream. This graph represents the subsequent subtraction of the remaining encapsulated drug present in the cycle from the initially provided amount to produce an indication of the amount of drug released.

Although these methods may seem to be theoretically suitable, in practice they are subject to multiple technical failures. Some of these difficulties arise due to the need to be able to distinguish the amount of drug that has been released from the drug retained in the nanoparticles. This is important because only the released drug can work for the subject. However, in practice, it has been demonstrated that there is a problem in accurately distinguishing and measuring the ability of two different drug "pools" (released and retained in the nanoparticle).

A significant difficulty associated with such techniques involves the difficulty of handling ex vivo samples containing drug-loaded nanoparticles. A number of factors can cause such nanoparticles to spontaneously release their encapsulated drugs and are released in a manner that does not accurately reflect the condition in the body. Such release occurs stepwise, for example, by diffusion of the drug molecules out of the nanoparticles, or by causing degradation of the "leakage" from the nanoparticles, or abruptly, if multiple conditions cause the plurality of nanoparticles to rupture. Such release may occur within the sample while waiting for analysis, or during the analysis process.

Only a small amount of such spontaneous release of the encapsulated drug significantly inevitably skews the map obtained in the measurement, resulting in an overestimation of the amount of drug released in the subject. Because as with The amount of drug that has been released in the nanoparticle is generally a large proportion of the total amount present in the sample (eg, blood source, such as blood or plasma), so only a small proportion of the naphthalene is present. Rice granules need to "burst" or "leak" in this way to cause a significantly inaccurate map.

Another difficulty that arises in connection with this approach is that the sensitivity of the measurement technique varies with respect to the amount being measured. Here, the large difference between the concentration of the drug to be measured remaining in the nanoparticle and the concentration of the drug that has been released (which tends to be much lower) adversely affects the accuracy of the selected measurement method. .

Another factor is the low solubility of AZD1152 hqpa.

When viewed on a whole, such difficulties can raise doubts about the accuracy with which such techniques can measure the amount of drug-loaded nanoparticles that are released and available to the subject. Therefore, there is a need to develop new methods that can avoid or mitigate at least some of these problems.

Pluim et al. (J Chromatography B, 877 (2009), 3549-3555) describe the simultaneous determination of AZD1152 and AZD1152 in human and mouse plasma and mouse tissues. Reversed phase liquid chromatography method.

Stern et al. (J Controlled Release, 172 (2013), 558-567) describe three docetaxel (including prodrugs) in bile duct cannulated rats. Comparative pharmacokinetic studies of related formulations, including nanomicelle micelle formulations.

In a first aspect, there is provided a method of measuring the amount of AZD1152 hqpa that is systemically released in a subject after administration of a nanoparticle comprising AZD1152 hqpa, the method comprising: • determining a sample from the subject, Determining the amount of metabolites of AZD1152 hqpa present in the sample; and • applying a pharmacokinetic model based on the determined amount of the metabolite to derive The amount of AZD1152 hqpa released systemically in the subject.

In a second aspect, there is provided a method of determining a release profile of a nanoparticle loaded with AZD1152 hqpa in a biological system having the ability to metabolize AZD1152 hqpa, the method comprising: • determining the derived organism from the first time point a sample of the system to determine the first amount of metabolite of the nanoparticle loaded with the AZD1152 hqpa present in the sample; • at a second time point, the sample from the biological system is determined to determine in the sample The second amount of the metabolite of the nanoparticle loaded with AZD1152 hqpa present; • based on the determined first amount and the second amount, applying a pharmacokinetic model to derive representative of the release at the first time point a first value of the amount of nanoparticle loaded with AZD1152 hqpa, and a second value representing the amount of nanoparticle of such load AZD1152 hqpa released at the second time point; and • using the first value and the The second value is used to generate a release profile of the nanoparticle of this load AZD1152 hqpa.

In a third aspect, there is provided a method of assessing the bioequivalence of a nanoparticle loaded with AZD1152 hqpa administered to a subject, the method comprising: determining a blood source sample from the subject to determine The amount of metabolite of the nanoparticle loaded with AZD1152 hqpa present in the sample; • based on the determined amount of the metabolite, applying a pharmacokinetic model to derive systemic release in the subject The amount of nanoparticle loaded with AZD1152 hqpa; and ● comparing the value of the amount of nanoparticle loaded with such a load AZD1152 hqpa systemically released in the subject with AZD1152 hqpa released from the second drug product Contrast value, and can be compared with other experimental parameters at will In combination, the bioequivalence of the nanoparticle loaded with AZD1152 hqpa and the second drug was evaluated.

In addition, the level of metabolites of AZD1152 hqpa was determined at different time points, providing an exposure profile for the metabolite. Direct comparison of such an exposure curve with a metabolite exposure curve from another drug product can be used as part of the bioequivalence assessment without the need to correlate metabolite levels with the level of released AZD1152 hqpa.

Accordingly, in a fourth aspect, there is provided a method of assessing bioequivalence of a nanoparticle loaded with AZD1152 hqpa administered to a subject, the method comprising: determining a blood source sample from the subject, Determining the amount of metabolite of such a nanoparticle loaded with AZD1152 hqpa present in the sample; - comparing the amount of the metabolite thus obtained with the same metabolite released from the second drug product comprising AZD1152 hqpa The values were compared and optionally combined with other comparative experimental parameters to assess the bioequivalence of the nanoparticle loaded with AZD1152 hqpa and the second drug.

In a fifth aspect, there is provided a method of determining an exposure profile of a metabolite of AZD1152 hqpa in a nanoparticle loaded with AZD1152 hqpa in a biological system having the ability to metabolize AZD1152 hqpa, the method comprising: Point, the sample from the biological system is determined to determine the first amount of the metabolite of the nanoparticle loaded with the AZD1152 hqpa present in the sample; • at the second time point, the sample from the biological system is determined, A second amount of metabolite of such a nanoparticle loaded with AZD1152 hqpa present in the sample is determined; and • the first value and the second value are used to generate an exposure profile for the metabolite.

The disclosure herein is based, at least in part, on the discovery by the inventors that it is associated with systemic release of measured drugs (eg, AZD1152 hqpa loaded in nanoparticle). The difficulty can be overcome by measuring the level of drug metabolites in the sample from the subject to whom the drug has been administered. This method of indirect measurement provides a number of benefits over the techniques that have been previously described.

The methods described herein allow for the amount of AZD1152 hqpa that is actually systemically released by the nanoparticles in the subject, since only this portion of the drug can be processed to produce the metabolites that are evaluated in the methods of the invention. .

Although not all released AZD1152 hqpa will be systemically released in the subject, and not all systemically released AZD1152 hqpa will be metabolized by the subject, but the pharmacokinetic model takes this into account, and Allows accurate determination of AZD1152 hqpa that has been systemically released (released and becomes systemically available).

The methods described herein also avoid the problems associated with the sensitivity of processing nanoparticles, measurement techniques that have caused difficulties in prior methods. Even in the case of a broken or leaked nanoparticle loaded with AZD1152 hqpa, this will not cause inaccurate contamination because the drug itself is not measured, but its metabolite. Similarly, there is no need to identify measurement techniques that provide suitable accuracy for both high and low concentrations of the compound, as only techniques that accurately measure the relative concentrations of metabolites need to be used.

The recognition that such methods can be used to accurately measure the amount of nanoparticle loaded with AZD1152 hqpa in a subject is led to the inventors' recognition that such a method can also be used to determine nanoparticles loaded with AZD1152 hqpa. Release curve, and can also be used to evaluate bioequivalence (whether comparing the nanoparticle loaded with AZD1152 hqpa to another drug containing AZD1152 hqpa serving as a standard, or comparing the second drug with the standard) Load AZD1152 hqpa nano particles). The methods described herein are particularly convenient for assessing bioequivalence as they can be performed on biological samples (e.g., blood or plasma, as described herein) that are readily (and repeatedly) obtained from a patient. The skilled person will understand that as described below, the load may be required Additional testing of AZD1152 hqpa nanoparticle formulations compared to other aspects of potentially bioequivalent formulations to demonstrate organisms with standards required by regulatory agencies that control drug registration (eg, US Food and Drug Administration) Equivalence.

A "bioequivalent form" of a composition as referred to herein is intended to mean a form of the composition that has or may be a regulatory body based on a bioequivalent (ie having the same biological effect) composition. Grant a marketing license.

The definitions of certain terms as used herein are provided below, followed by an exemplary equation describing the relationship between different parameters that allow the derivation of the amount of nanoparticles of the load AZD1152 hqpa based on determining the amount of metabolite present. Detailed description. Exemplary methods and specific non-limiting examples that further illustrate various aspects are further provided below.

definition "Nano particles"

As mentioned in the "Background" section above, nanoparticle has recently become an increasingly popular agent for drug delivery due to the advantageous properties of nanoparticles in tissue distribution and controlled delivery. For the purposes of the present disclosure, nanoparticle can be considered to be any particle that can be used to encapsulate AZD1152 hqpa, having a size between 1 and 150 nm, such as between 1 and 130, such as between 50 and 130 nm, such as 1 And the size between 100nm.

In a suitable embodiment, the nanoparticles can be considered to be any particles that can function in a manner that is bioequivalent to the nanoparticles exemplified herein. For example, such potentially bioequivalent particles can release AZD1152 hqpa at a release rate comparable to the nanoparticles exemplified herein.

In a suitable embodiment, for the purposes of the present disclosure, the nanoparticles may be composed of a material selected from the group consisting of diblock poly(lactic)-poly(ethylene) glycol copolymers; And a diblock poly(lactic-co-glycolic acid copolymer)-poly(ethylene) glycol copolymer.

Nanoparticles encompassing AZD1152 hqpa may encompass drugs that are combined with, or substantially independent of, one or more additional compounds. In a suitable embodiment, AZD1152 hqpa can be combined with another compound that forms a hydrophobic ion pair with AZD1152 hqpa. For example, AZD1152 hqpa can be combined with a substantially hydrophobic acid in the nanoparticle. Suitably, the hydrophobic acid may be selected from the group consisting of deoxycholic acid; cholic acid; dioctyl sulfosuccinic acid; oleic acid;

Any of the above considerations are suitable for encapsulating nanoparticles of AZD1152 hqpa.

In a suitable embodiment, the method of the invention comprises the step of administering a nanoparticle comprising AZD1152 hqpa to a subject. This administration can be carried out using any suitable route. In a suitable embodiment, a nanoparticle comprising AZD1152 hqpa is administered intravenously to a subject.

In a specific embodiment, suitable nanoparticles comprising AZD1152 hqpa are described in those of WO 2015/036792, in particular those exemplified in WO 2015/036792, and in particular in WO 2015/ A formulation comprising oxalic acid exemplified in 036792.

For example, suitable nanoparticles include therapeutic nanoparticles comprising AZD1152 hqpa, pamoic acid, and diblock poly(lactic)-poly(ethylene) glycol copolymers (wherein the therapeutic The nanoparticle comprises from about 10 to about 30% by weight of the poly(ethylene) glycol, and the poly(lactic) acid-poly(ethylene) glycol copolymer has a poly(lactic acid) having a number average molecular weight of about 16 kDa and a number average Poly(ethylene) glycol having a molecular weight of about 5 kDa.

For example, suitable nanoparticles include therapeutic nanoparticles comprising from about 12 to about 25 weight percent AZD 1152 hqpa, from about 7 to about 15 weight percent pamoate, and diblock poly (milk) An acid-poly(ethylene) glycol copolymer (wherein the therapeutic nanoparticle comprises from about 10 to about 30% by weight of a poly(ethylene) glycol, and the poly(lactic) acid-poly(ethylene) glycol copolymer The material has a poly(lactic acid) having a number average molecular weight of about 16 kDa and a poly(ethylene) glycol having a number average molecular weight of about 5 kDa.

For example, suitable nanoparticles include therapeutic nanoparticles, the therapeutic nanoparticles The granules comprise from about 15 to about 25% by weight of AZD1152 hqpa, from about 7 to about 15% by weight of pamoic acid, and a diblock poly(lactic)-poly(ethylene) diol copolymer (wherein the therapeutic nanoparticle) The poly(ethylene) glycol is included in an amount of from about 10 to about 30% by weight, and the poly(lactic) acid-poly(ethylene) glycol copolymer has a poly(lactic acid) having a number average molecular weight of about 16 kDa and a number average molecular weight of about 5kDa poly(B) diol).

For the purposes of the above suitable nanoparticles, the term "about" refers to a digit of <10, +/- 0.5, and refers to a digit of 10 or greater, +/- 1.

"AZD1152 hqpa"

AZD1152 hqpa used throughout the disclosure refers to the compound (2-(3-((7-(3-(ethyl(2-hydroxyethyl))amino)) oxy) quinazolin-4-yl)) -1H-pyrazol-5-yl)-N-(3-fluorophenyl)acetamidine).

"AZD1152"

Sometimes, this specification refers to AZD1152. These references should be considered for the compound (2-(ethyl(3-((4-())))))) 1H-Pyrazol-3-yl)amino)quinazolin-7-yl)oxy)propyl)amino)ethyldihydrophosphate).

"Second" (or "another") "drug (or product) containing AZD1152 hqpa"

The second (or another) drug (or product) comprising AZD1152 hqpa can serve as a source of AZD1152 hqpa and is not necessarily limited to an article of another nanoparticle formulation, provided that it releases AZD1152 hqpa and it can be, for example, polymerized AZD1152 hqpa spontaneously leaks during sample processing or analysis of the conjugate or dendrimer.

"Systemically released"

For the purposes of this disclosure, if AZD1152 hqpa has been released from the nanoparticle in the subject, such that AZD1152 hqpa can then be metabolized by the subject, then the nanoparticle loaded with AZD1152 hqpa can be referred to as "systemic" Release." It will be appreciated that for the purposes of the present disclosure, AZD1152 hqpa not released from the nanoparticles cannot be said to have been systemically released. There is another situation that cannot be called systemic release, that It is in some cases, such as where it cannot be metabolized by the subject, AZD1152 hqpa has been released from the nanoparticles.

"subject"

For the purposes of this disclosure, the subject can be any animal that has been administered a nanoparticle loaded with AZD 1152 hqpa.

In a suitable embodiment, the subject is a human. Suitable human subjects, as the context requires, may be individuals involved in a clinical trial investigating the characteristics of such nanoparticles loaded with AZD1152 hqpa, such as bioavailability. Alternatively or additionally, a suitable human subject may be an individual who has undergone treatment with nanoparticle loaded with AZD1152 hqpa.

In an alternate embodiment, the subject is a non-human animal. In a suitable embodiment, the non-human animal can be an animal for preclinical investigation of nanoparticle loaded with AZD1152 hqpa. By way of example only, a non-human animal can be a rodent, such as a rat.

The skilled person will understand how to adapt the model to different subject species.

"sample"

The sample from the subject provides a sample of information representative of the metabolism in the subject. The sample will be a sample capable of retaining the metabolite of AZD1152 hqpa. In particular, the sample may be a sample of a metabolite capable of retaining AZD 1152 hqpa (eg, hqpa desfluoraniline) (described further herein, and also referred to as AZ 12102238).

In a suitable embodiment, the sample is taken from a sample of the subject. Such samples may be suitable for in vitro or ex vivo analysis.

In any embodiment, the sample may be suitably selected from the group consisting of: a tissue sample; and a body fluid sample. A suitable example of a body fluid sample may be selected from the group consisting of: a blood sample; a serum sample; a plasma sample; a urine sample; Lymph samples; interstitial fluid samples; bile samples; saliva samples; and stool samples. It will be appreciated that a variety of different sample types may be derived from blood, including blood samples, serum samples, and plasma samples. For the purposes of this disclosure, each of these sample types can be considered a "blood source sample."

In one embodiment, the sample is a blood sample. In another embodiment, the sample is a plasma sample. In another embodiment, the sample is a serum sample.

In another embodiment, the sample is a urine sample. In another embodiment, the sample is a stool sample.

In a suitable embodiment, the method of the invention may comprise the step of taking one or more samples to be determined.

It will be appreciated that the time elapsed between administration of the nanoparticle comprising AZD1152 hqpa and taking the sample will affect the amount of nanoparticle loaded with AZD1152 hqpa that will have been systemically released in the subject. The first sample can generally be taken after a period of time sufficient to allow AZD 1152 hqpa to be released and metabolized to an accurately quantifiable extent has elapsed.

In embodiments in which multiple samples are taken over a time course, the amount due to the different samples can provide information about the release of AZD1152 hqpa over time. Suitably, the sample can be taken at one or more time points after giving the following considerations of the nanoparticle comprising AZD1152 hqpa.

The appropriate time course for sampling will depend on both the pharmacokinetics of the AZD1152 hqpa and the specific nanoparticle formulation in the particular species, as well as the time elapsed with the administration of AZD1152 hqpa. Using AZD1152 hqpa administered to rats or mice by intravenous bolus as an example, a suitable sampling schedule will utilize the following time points: 5, 10 after administration of a prodrug, active drug or metabolite drug And 30 minutes and 1, 3, 6, 24, 30 and 48 hours, and 5, 10 and 30 minutes and 1, 6, 24, 72, 168, 240, 336, 432 and 504 hours after the administration of the nanoparticle formulation .

A similar time course for sampling can be applied to humans, but sampling can be The continuation is slightly longer. For example, for AZD1152 hqpa administered to humans by intravenous bolus injection, a suitable sampling schedule can utilize the following time points: 5, 10 and 30 minutes and 1, 3, after administration of the prodrug, active drug or metabolite drug. 6, 24, 30, 48 and 72 hours, and 5, 10 and 30 minutes and 1, 6, 24, 72, 168, 240, 336, 432, 504 and 672 hours after administration of the nanoparticle formulation.

The skilled artisan will appreciate that the above example sampling schedules (more/less/different times) may be adapted for convenience, and such variations are within the scope of the methods described herein.

"Metabolites"

For the purposes of this disclosure, metabolites should be considered to encompass any compound produced by the metabolism of nanoparticles loaded with AZD1152 hqpa.

Suitably, any metabolite of AZD1152 hqpa can be used. However, the inventors have discovered that certain metabolites have properties that confer significant advantages in methods of utilizing such metabolites.

In a suitable embodiment, the metabolite is selected from the group consisting of 2-(3-((7-(3-(ethyl(2-hydroxyethyl))amino)propoxy) Quinazolin-4-yl)amino)-1H-pyrazol-5-yl)acetic acid (also known as AZD1152 hqpa desfluoroaniline, or AZ12102238); AZD1152 hqpa defluoroaniline N-acetic acid; AZD1152 Hqpa N-acetic acid; AZD1152 hqpa N-oxide; and AZD1152 hqpa N-deethyl. The inventors have discovered that such metabolites of AZD1152 hqpa are generally formed in sufficient amounts for metabolites to be accurately measured in the methods of the invention.

The full name and structure of the compounds are shown below: AZD1152 hqpa defluoroaniline (AZ12102238): 2-(3-((7-(3-(ethyl(2-hydroxyethyl))amino)propoxy)) Quinazolin-4-yl)amino)-1H-pyrazol-5-yl)acetic acid:

AZD1152 hqpa defluoroaniline N-acetic acid: 2-[5-[[7-[3-[carboxymethyl(ethyl)amino]propoxy]quinazolin-4-yl]amino]-1H- Pyrazol-3-yl]acetic acid:

AZD1152 hqpa N-acetic acid: 2-[ethyl-[3-[4-[[3-[2-(3-fluoroanilino)-2-yloxy-ethyl]-1H-pyrazole-5- Amino]quinazolin-7-yl]oxypropyl]amino]acetic acid:

AZD1152-hqpa N-desethyl: N-(3-fluorophenyl)-2-[5-[[7-[3-(2-hydroxyethylamino)propoxy]quinazoline-4- Amino]-1H-pyrazol-3-yl]acetamide:

AZD1152-hqpa N-oxide: N-ethyl-3-[4-[[3-[2-(3-fluoroanilino)-2-yloxy-ethyl]-1H-pyrazole-5- Amino]quinazolin-7-yl]oxy-N-(2-hydroxyethyl)propane-1-amine oxide:

In a suitable embodiment, the metabolite is selected from the group consisting of AZD1152 hqpa defluoroaniline; and AZD1152 hqpa defluoroaniline acetic acid. The inventors have discovered that these metabolites of AZD1152 hqpa are formed by one or both of human and rat subjects that allow rapid modeling between such important clinical and preclinical species.

In a suitable embodiment, the selected metabolite is one of a consistent form within a different patient population. This provides a significant advantage in the confidence that it can be placed in results produced within multiple patient populations.

In a suitable embodiment, the selected metabolite is a metabolite formed only by the body's action on the released active AZD1152 hqpa, and thus the presence of metabolites occurs only for drugs that have been systemically released and metabolized.

In a suitable embodiment, the selected metabolites exhibit clearance and distribution volume metabolites within the biological system that facilitate their collection and accurate analysis.

In a suitable embodiment, the selected metabolite is readily synthesizable, allowing for the production of a sufficient amount to produce a metabolite of a standard curve that contributes to the quantification of metabolites in the sample.

Suitable metabolites for use in the methods of the invention should not be significant decomposition products of AZD1152 hqpa that can be formed in nanoparticles that are free of AZD1152 hqpa that require systemic release and metabolism. A suitable metabolite for use in the method of the invention should not be a significant impurity in the AZD1152 hqpa formulation, which would otherwise be detected without the need for systemic release and metabolism of AZD1152 hqpa.

In one embodiment, the metabolite for measurement is 2-(3-((7-(3-(ethyl(2-hydroxyethyl))amino)propoxy)quinazolin-4-yl)) Amino)-1H-pyrazol-5-yl)acetic acid, which is also known as AZ12102238 or AZD1152 hqpa defluoroaniline.

Suitable processes for the manufacture of AZD1152 hqpa defluoroaniline and AZD1152-hqpa N-oxide are set forth in the examples that follow. Suitable processes for the manufacture of other metabolites described in this section will be readily understood by the skilled person to be similar to the conventional chemistry required for the application, for the manufacture of AZD1152 hqpa or AZD1152 hqpa defluoroaniline, or other similarities known in the art. A known process for compounds.

In another aspect, an isolated synthetic sample of a metabolite of AZD1152 hqpa is provided. In one embodiment, the isolated synthetic sample is 2-(3-((7-(3-(ethyl(2-hydroxyethyl))amino)propoxy)quinazolin-4-yl)) A sample of the amino)-1H-pyrazol-5-yl)acetic acid. In another embodiment, the isolated sample is 2-[5-[[7-[3-[carboxymethyl(ethyl)amino]propoxy]quinazolin-4-yl]amino) a sample of -1H-pyrazol-3-yl]acetic acid. In another embodiment, the isolated sample is 2-[ethyl-[3-[4-[[3-[2-(3-fluoroanilinido)-2-yloxy-ethyl]-) A sample of 1H-pyrazol-5-yl]amino]quinazolin-7-yl]oxypropyl]amino]acetic acid. In another embodiment, the isolated sample is N-(3-fluorophenyl)-2-[5-[[7-[3-(2-hydroxyethylamino)propoxy] quinazoline A sample of phenyl-4-yl]amino]-1H-pyrazol-3-yl]acetamide. In another embodiment, the isolated sample is N-ethyl-3-[4-[[3-[2-(3-fluoroanilino)-2-oxo-ethyl]-1H- A sample of pyrazol-5-yl]amino]quinazolin-7-yl]oxy-N-(2-hydroxyethyl)propan-1-amine oxide. It should be understood that the isolated synthetic sample is a sample that has been made in vitro from humans or animals.

In another aspect, there is provided the use of a metabolite of AZD1152-hqpa in an analytical method for measuring AZD1152 hqpa in a biological sample. Suitably, the analytical method is an HPLC method as described below. In a suitable embodiment, the metabolite is selected from the group consisting of AZD1152 hqpa defluoroaniline; and AZD1152 hqpa defluoroaniline acetic acid.

In another aspect, there is provided the use of a metabolite of AZD1152 in determining an in vivo release profile of AZD1152 hqpa from a pharmaceutical product comprising AZD1152 hqpa in a human or non-human animal to which the pharmaceutical product has been administered. In a suitable embodiment, the metabolite is selected from the group consisting of AZD1152 hqpa defluoroaniline; and AZD1152 hqpa defluoroaniline acetic acid.

In another aspect, there is provided an in vivo release profile of an isolated synthetic sample of a metabolite of AZD1152 in a human or non-human animal to which the pharmaceutical product has been administered, in determining the metabolite from a pharmaceutical product comprising AZD1152 hqpa Use in. In a suitable embodiment, the metabolite is selected from the group consisting of AZD1152 hqpa defluoroaniline; and AZD1152 hqpa defluoroaniline acetic acid.

“Measurement of Nanoparticles for Load AZD1152 hqpa” or “Measurement of Samples for Metabolites”

Suitably, the method used in the determination of the sample for nanoparticles loaded with AZD1152 hqpa or the determination of the sample for metabolites (eg AZ12102238) is liquid chromatography-mass spectrometry (LC-MS).

In a suitable embodiment, the method used in the determination of a sample for a nanoparticle loaded with AZD1152 hqpa or the determination of a sample for a metabolite (eg AZ12102238) is liquid chromatography-mass spectrometry (LC) -MS) technology. LC-MS techniques can be advantageously used because they are capable of distinguishing closely related compounds from each other, such as metabolites and drugs that are sources of such metabolites. The LC-MS technique is also very well suited for discriminating a variety of compounds, such as nanoparticle or metabolites loaded with AZD1152 hqpa in a complex mixture of those found in samples derived from animal subjects. Details of suitable parameters that can be used for such LC-MS techniques are further described in the examples of this specification when assaying samples for AZ12102238 or for AZD1152 hqpa.

In a suitable embodiment, the sample is used to measure the sample against nanoparticles loaded with AZD1152 hqpa or against the metabolite (eg AZ12102238) The method used in the assay was a mass spectrometry (MS) imaging technique. In the method of the invention in which the sample is a tissue sample, the use of MS imaging techniques for determining the sample against metabolites or nanoparticles loaded with AZD1152 hqpa would be of particular utility.

"Determining the amount of nanoparticle present in the load AZD1152 hqpa" or "determining the amount of metabolite present"

The method of the present invention can utilize any suitable technique that allows for the determination of the amount of nanoparticle or metabolite (e.g., AZ12102238) loaded with AZD1152 hqpa in the sample. Suitably, the method of the invention allows for the determination of the amount of nanoparticle or metabolite loaded with AZD1152 hqpa in the sample by a technique in which the sample is compared to a standard curve prepared using a series of concentrations of AZD1152 hqpa or metabolite.

As discussed further above, the ability to make a sufficient amount of metabolites to allow for the generation of a standard curve is a benefit of the method of using metabolite AZ12102238.

The first aspect of the method can be modified at will

The method of the first aspect can also include the step of determining a sample from the subject to determine the amount of AZD1152 hqpa present in the sample. AZD1152 hqpa can be retained in the nanoparticle. The amount thus determined can be used in the applied pharmacokinetic model to derive the amount of systemically released AZD1152 hqpa in the subject. Suitably, the amount thus determined can be used in a population pharmacokinetic model.

With reference to metabolites, the assays and determination methods described herein are also generally applicable to (where necessary modifications can be made) procedures for the practice of AZD1152 hqpa.

In the Examples section of this specification, an illustrative example of such a method that can determine the presence of AZD 1152 hqpa in a sample and determine the amount of this compound present is provided.

In a suitable embodiment of such a method, the sample from which the metabolite is determined and the sample from which the amount of AZD1152 hqpa is determined are derived from the same sample. In an alternate embodiment, the sample from which the metabolite is determined and the sample from which the amount of AZD1152 hqpa is determined are different samples.

The second aspect, or the method of the third aspect, can be modified at will

The method of the second aspect or the third aspect may further comprise the step of determining a sample from the subject to determine the amount of nanoparticle loaded with AZD1152 hqpa present in the sample. Nanoparticles loaded with AZD1152 hqpa can be retained in the nanoparticles. The amount thus determined can be used in the applied pharmacokinetic model to derive the amount of nanoparticle loaded with AZD1152 hqpa that has been systemically released in the subject. Suitably, the amount thus determined can be used in a population pharmacokinetic model.

With reference to metabolites and with reference to the exemplary loaded drug AZD1152 hqpa of nanoparticle, the assays and determination methods described herein are also generally applicable (where modifications may be made) with respect to other loaded drugs (eg, in the third aspect of the invention or The second drug considered in the method of the fourth aspect) is subjected to a procedure of practice.

In the Examples section of this specification, an illustrative example of such a method that can determine the presence of a nanoparticle loaded with AZD1152 hqpa in a sample, and the amount of such a nanoparticle of such a load AZD1152 hqpa present is provided.

The second and fifth aspects of the method can be modified at will (where applicable)

As further discussed above, the second aspect provides a method of determining a release profile of a nanoparticle of a load AZD1152 hqpa, the method comprising determining a sample from a biological system at a first time point and a second time point to determine the presence of the sample The amount of metabolite, and thus the first and second values representing the amount of nanoparticle of the load AZD1152 hqpa released at the corresponding time point. This value is then used to generate a release profile.

The same data can be used to generate an exposure curve for metabolites without further deriving the amount of AZD1152 hqpa. It will be understood that the term "exposure curve" refers to a graph of the amount of metabolite present in a sample at multiple time points.

In a suitable embodiment, the method of this second aspect may further involve determining a sample from the biological system at a third or subsequent time point to determine a load AZD1152 hqpa present in the sample at the third or subsequent time point. Metabolite of nanoparticle the amount. A pharmacokinetic model was then applied to derive a third value representative of the amount of nanoparticle of the load AZD1152 hqpa released at the third time point, and this third value was used to generate a release profile of the nanoparticle loaded with AZD1152 hqpa.

It will be appreciated that the method can include fourth, fifth, sixth, seventh, eighth, ninth, tenth, and other samples from respective time points, and that the samples can be used to derive a release curve that can be used to generate a release profile. Fourth, fifth, sixth, seventh, eighth, ninth, tenth and other values.

It will be appreciated that similarly, the amount of metabolite at any third or subsequent time point can be used to generate an exposure profile for the metabolite of the fifth aspect of the invention.

In a suitable embodiment, the method of the second or fifth aspect may comprise the step of introducing into the biological system an amount of nanoparticle comprising AZD1152 hqpa.

In a suitable embodiment, the biological system having the ability to metabolize AZD1152 hqpa can be an in vivo system. Such in vivo systems will utilize individual animals (human or other animals) as considered elsewhere in this disclosure. In a suitable embodiment, the samples obtained from such an in vivo system can be of various types encompassed herein, including blood, serum, or plasma samples.

Alternatively, a biological system having the ability to metabolize AZD1152 hqpa can be an in vitro system. Such an in vitro system can utilize biological cells maintained in culture. The biological cells can be liver cells. Alternatively, the in vitro system can use cell fragments, such as liver microsomes; cell parts, such as the liver S9 portion; or culture with an enzyme, such as a particular enzyme isotype. In the case of such an in vitro method, a suitable sample obtained from the system can include a medium in which the biological cells are cultured.

The method of the second or fifth aspect can be suitably used in a quality assurance scheme. By way of example only, it is contemplated that the method according to the second or fifth aspect of the invention can be used to ensure consistency between different batches of nanoparticle having AZD1152 hqpa.

The third and fourth aspects (if applicable) can be modified at will.

As with the method of the second aspect considered above, in a suitable embodiment, the third aspect method can utilize multiple time points to acquire a sample. A plurality of samples generated in this manner can be used to derive the amount of nanoparticle loaded AZD1152 hqpa that is systemically released at the different time points, and use the same amount to generate a curve for the amount of released AZD1152 hqpa (eg, Concentration curve). This information regarding the concentration of hZpa at AZD1152 with these time points can be used to assess the bioequivalence of the nanoparticle and the second drug loaded with AZD1152 hqpa. Similarly, for a fourth aspect, in a suitable embodiment, the method of the fourth aspect can utilize a plurality of time points to acquire a sample and use the equal amount to generate an amount of the formed AZD1152 hqpa metabolite. Curve (eg concentration curve / exposure curve).

In a suitable embodiment, the value of the amount of nanoparticle loaded AZD1152 hqpa or the amount of metabolite of AZD1152 hqpa based on systemic release in the subject (compared to the comparison value with respect to the second drug) may be The following groups of components are selected: area under the curve (AUC); peak concentration ( _Cmax ); and peak concentration time ( _Tmax ).

In a suitable embodiment, such a method of the invention is carried out on nanoparticle loaded with AZD 1152 hqpa administered to one or more individuals at different doses.

The same procedure can be performed for the second drug practice with the nanoparticle loaded against AZD1152 hqpa (including determining the sample from the subject to determine the metabolite of the nanoparticle loaded with AZD1152 hqpa present in the sample) And, (for the third aspect) applying a pharmacokinetic model to derive a systemically released amount of nanoparticle loaded AZD1152 hqpa based on the determined amount of the metabolite) to generate a contrast value.

In a suitable embodiment, the second drug is also a drug-loaded nanoparticle.

The subject for use in the method according to the third or fourth aspect of the invention may be selected with reference to conventional criteria in the field of assessing bioequivalence. For example, a subject can be selected for a specific classification based on gender, age, or ethnicity. A suitable way may be to use a group of subjects that reference one or more of the criteria considered above to be identical to each other, or may use Choose to include groups of desired levels of diversity relative to different criteria.

In a suitable embodiment of the method of the invention (whether the first aspect, the second aspect or the third aspect) wherein the amount of nanoparticles supporting the load AZD1152 hqpa is determined, it may preferably be for two or Samples collected at more time points to determine the relevant amount. Such an embodiment of the method of the invention makes it possible to produce a concentration profile of nanoparticles loaded with AZD 1152 hqpa over time. Such curves can then be used in pharmacokinetic models. Such an embodiment is useful because it can provide additional information about the release of AZD1152 hqpa prior to metabolism. Similarly for the fourth aspect, the relative amount of metabolite can be determined for samples collected at two or more time points. Such an embodiment of the method of the invention makes it possible to generate a concentration profile of the metabolite over time.

Bioequivalence assessment of the third or fourth aspect of the invention may require measurement of other contrast parameters, which may depend on the type of cancer being treated. For example, by measuring biomarkers (eg, pHH3, see examples in WO 2015/036792), exposure levels in target tissues (eg, levels in tumors or bone marrow, etc.), efficacy (reaction rate), imaging (eg by mass spectrometry), or by measuring the properties of the nanoparticle (eg, particle size as measured by dynamic light scattering, in vitro release (or dissolution) of the drug from the nanoparticle). Regulators (such as the US Food and Drug Administration) may issue guidelines on how to evaluate the bioequivalence of new products, such as the nanoparticle docetaxel reproduced in the reference examples below. Draft guidelines.

In one embodiment of the third aspect, there is provided a method of assessing the bioequivalence of a nanoparticle loaded with AZD1152 hqpa administered to a subject having a solid tumor disease, the method comprising: a blood source sample of the subject to determine the amount of metabolite of the nanoparticle loaded with the AZD1152 hqpa present in the sample; • based on the determined amount of the metabolite, applying a pharmacokinetic model to derive The subject is a systemically released nanoparticle of this load AZD1152 hqpa The amount of particles; and - comparing the value of the amount of nanoparticle loaded with such a load AZD1152 hqpa systemically released in the subject with respect to AZD1152 hqpa released from the second drug product, and optionally The bioequivalence of the nanoparticle loaded with AZD1152 hqpa and the second drug was evaluated in conjunction with one or more additional comparative experimental parameters.

In another embodiment of the third aspect, there is provided a method of assessing the bioequivalence of a nanoparticle loaded with AZD1152 hqpa administered to a subject having hematological cancer, the method comprising: a blood source sample of the subject to determine the amount of metabolite of the nanoparticle loaded with the AZD1152 hqpa present in the sample; • based on the determined amount of the metabolite, applying a pharmacokinetic model to derive The amount of such a nanoparticle loaded with AZD1152 hqpa that is systemically released in the subject; and • comparing the amount of nanoparticle based on the amount of such loaded AZD1152 hqpa that is systemically released in the subject Regarding the comparative value of AZD1152 hqpa released from the second drug product, and optionally combining with one or more additional comparative experimental parameters, thereby evaluating the nanoparticle of the load AZD1152 hqpa and the organism of the second drug, etc. Effectiveness.

Accordingly, in a fourth aspect, there is provided a method of assessing the bioequivalence of a nanoparticle loaded with AZD1152 hqpa administered to a subject having a solid tumor disease, the method comprising: • determining from the subject a blood source sample to determine the amount of metabolite of the nanoparticle loaded with AZD1152 hqpa present in the sample; - comparing the amount of the metabolite thus obtained with respect to the second drug from HZpa containing AZD1152 The contrast value of the same metabolite released by the product, and optionally The other comparative experimental parameters were combined to evaluate the bioequivalence of the nanoparticle loaded with AZD1152 hqpa and the second drug.

Accordingly, in a fourth aspect, there is provided a method of assessing the bioequivalence of a nanoparticle loaded with AZD1152 hqpa administered to a subject having hematological cancer, the method comprising: • determining from the subject a blood source sample to determine the amount of metabolite of the nanoparticle loaded with AZD1152 hqpa present in the sample; - comparing the amount of the metabolite thus obtained with respect to the second drug from HZpa containing AZD1152 The comparative values of the same metabolites released by the product, and optionally combined with other comparative experimental parameters, thereby assessing the bioequivalence of the nanoparticle loaded with AZD1152 hqpa and the second drug.

Suitable examples of solid tumor diseases include prostate cancer, gastric cancer, colorectal cancer, skin cancer (such as melanoma or basal cell carcinoma), lung cancer (such as non-small cell lung cancer (NSCLC), small cell lung cancer (SCLC)), breast cancer. , ovarian cancer, head and neck cancer, bronchial cancer, pancreatic cancer, bladder cancer, brain cancer or central nervous system cancer, peripheral nervous system cancer, esophageal cancer, oral cancer or pharyngeal cancer, liver cancer ( such as hepatocellular carcinoma), kidney cancer (eg, renal cell carcinoma), testicular cancer, cholangiocarcinoma, small intestine or appendix cancer, gastrointestinal stromal tumor, salivary gland cancer, thyroid cancer, adrenal cancer, osteosarcoma, chondrosarcoma, and the like. In one embodiment, the solid tumor disease is selected from the group consisting of NSCLC, SCLC, ovarian cancer, and colorectal cancer.

Suitable examples of hematological cancer include chronic myelogenous leukemia, chronic myelomonocytic leukemia, Philadelphia chromosome positive acute lymphoblastic leukemia, mantle cell lymphoma, acute myeloid leukemia, diffuse Large B-cell lymphoma, myeloma, peripheral T-cell lymphoma, and myelodysplastic syndrome. In one embodiment, the hematological cancer is selected from the group consisting of AML, DLBCL, and myelodysplastic syndrome.

Pharmacokinetic models suitable for use in these methods

The skilled artisan will be able to readily select a suitable pharmacokinetic model by which the amount of AZD1152 hqpa that produces the metabolite can be derived using the amount of metabolite determined to be present in the sample. An illustration of a suitable pharmacokinetic model for use in the methods of the invention is provided below.

For modeling purposes, encapsulated drugs in the nanoparticles of the body are treated as small molecules. The amount of the drug, both in the body and in the nanoparticles, is treated in the same manner as the small molecule. In this model, the clearance of the encapsulated drug, both in vivo and in the nanoparticle, involves any process that reduces the amount of active drug both in the body and in the nanoparticle, which can be considered as Group mechanism. The first group of clearance mechanisms are those that cause release of the active drug into the body, and may include mechanisms such as diffusion from intact nanoparticles, leaving intact nanoparticles containing less drug; or cleavage of individual nanoparticles. Some or all of the active drug inside the nanoparticle is released into the body, leaving nanoparticle containing less drug in the body. The second group of clearance mechanisms are those that do not release the active drug into the body, and may include the following mechanisms: loss of intact drug-containing nanoparticle from the body; or when the intact active drug is contained in the nanoparticle or in the nanoparticle When destroyed, chemical changes occur in intact active drugs.

An exemplary combined pharmacokinetic model for the release of an active drug from a nanoparticle (eg, AZD1152 hqpa) consists of four sub-models. These submodels are all standard pharmacokinetic papillary compartment models, each consisting of a central compartment and multiple peripheral compartments. The central compartment is connected to remove a dose of the drug in both the body and the nanoparticle in a certain ratio to increase the amount of active drug in the active drug central chamber. Because AZD1152 is a prodrug, the prodrug central chamber is connected to the active drug center compartment, so that the prodrug is cleared in a certain proportion to increase the amount of active drug in the active drug center chamber. In the general case, the drug administered in the form of a prodrug only requires the prodrug portion of the model. It should be understood that the "prodrug" referred to in this section shall mean AZD1152. Similarly, the activity is cleared in a certain ratio The drug (AZD1152 hqpa) increased the amount of metabolites in the metabolite central chamber. It should be understood that the "active drug" referred to in this section shall mean AZD1152hqpa.

AZD1152 is included in the model used below because it provides additional data to increase the robustness of the model, but analysis of the release of AZD1152 hqpa from nanoparticles by AZD1152 is generally not required by the methods described herein.

In a suitable rat model for AZD1152, the number of peripheral compartments is 1 for prodrugs, drugs and metabolites contained in nanoparticles, and 2 for active drugs, however, for each group The exact number of peripheral compartments will depend on the compound and metabolite being discussed, the species used, and the amount and quality of available data. One of ordinary skill in the art will be able to determine the appropriate number of peripheral compartments without any undue experimentation or without the need to perform an inventive activity.

Suitable rat model

A suitable model of AZD1152hqpa that can be used in rats is shown mathematically below.

For active drugs that are both in the body and contained in the nanoparticles:

Wherein: V _n1 is the apparent volume of the distribution of the central compartment of the nanoparticle; V _n2 is the apparent volume of the distribution of the compartment surrounding the nanoparticle; C _n1 is both in vivo and contained in the nanoparticle and in the nai The concentration of the drug in the central compartment of the rice granule; C _n2 is the concentration of the drug in both the body and the nanoparticle and in the compartment surrounding the nanoparticle; CL _n is both in vivo and in the nanoparticle Drug within the clearance from the central compartment of the nano particles; Q _n is contained in both in vivo and atrioventricular clearance or flow of drug particles in the nanometer nano particles between the central compartment and the peripheral compartment of The input _n is a function describing the input of the drug from both the in vivo and the nanoparticle administered from the nanoparticle formulation; dC _n1 /dt and dC _n2 /dt are C _n1 and C _n2 over time, respectively Rate of change.

For prodrugs: Where: V _p1 is the apparent volume of the distribution of the central compartment of the prodrug; V _p2 is the apparent volume of the distribution of the peripheral compartment of the prodrug; C _p1 is the concentration of the prodrug in the atrioventricular center; C _p2 is The concentration of prodrug in the peripheral compartment of the prodrug; CL _p is the clearance rate of the prodrug from the center of the prodrug; Q _p is the interventricular clearance or flow rate of the prodrug between its center and the surrounding compartment; _p is a function describing the prodrug input from the prodrug; dC _p1 /dt and dC _p2 /dt are the rates of change of C _p1 and C _p2 over time, respectively.

For active drugs: Where: V _a1 is the apparent volume of the distribution of the central compartment of the active drug; V _a2 is the apparent volume of the distribution of the peripheral compartment of the active drug 2; V _a3 is the apparent volume of the distribution of the surrounding compartment of the active drug No. 3 C _a1 is the concentration of the active drug in the _chamber of the active drug center; C _a2 is the concentration of the active drug in the peripheral compartment of the active drug No. 2; C _a3 is the concentration of the active drug in the peripheral compartment of the active drug No. 3; M _na is the clearance ratio of the drug which is released into the body both in the body and in the nanoparticle; M _pa is the clearance ratio of the prodrug which releases the active drug into the body; CL _a is the active drug from the active drug Clearance rate of central compartment; Q _a2 is the clearance or flow rate of active drug between the central compartment and the peripheral compartment of No. 2; Q _a3 is the active drug in its central compartment and the surrounding compartment of No. 3 Interventricular clearance or flux; input _a is a function describing the input of the active drug from the active drug; dC _a1 /dt, dC _a2 /dt and dC _a3 /dt are C _a1 , C _a2 and C respectively _The rate of change of _a3 over time.

For metabolites: Where: V _m1 is the apparent volume of the distribution of the central compartment of the metabolite; V _m2 is the apparent volume of the distribution of the compartment surrounding the metabolite; C _m1 is the concentration of the metabolite in the atrioventricular compartment; C _m2 is The concentration of metabolites in the peripheral compartment of the metabolite; _Ma is the clearance ratio of the active drug that releases the metabolite into the body; CL _m is the clearance rate of the metabolite from the central compartment of the metabolite; Q _m is the metabolite in it Interventricular clearance or flow between the central and peripheral compartments; input _m is a function describing metabolite input from metabolites; dC _m1 /dt and dC _m2 /dt are C _m1 and C _{m2 , respectively} The rate of change over time.

In order to construct a model as described above, the following information is required: • concentration time data of the drug in both the body and the nanoparticle, and the active drug (AZD1152 hqpa) or metabolite after intravenous administration of the nanoparticles. Concentration time data of at least one; ● concentration time data of the prodrug and concentration time data of at least one of the active drug or metabolite after intravenous administration of the prodrug if a prodrug (ie, AZD1152) is used; Concentration time data of the drug (ie, AZD1152 hqpa) and concentration time data of metabolites after intravenous administration of the active drug; and ● concentration time data of total metabolite after intravenous administration of the metabolite.

If data after intravenous administration of metabolites are not available, the parameterization of the metabolite submodel needs to be altered in the following manner.

Wherein the following parameter is a composite parameter: V _m1 /M _am is the apparent volume of the distribution of the metabolite central compartment with respect to the clearance ratio of the active drug that releases the metabolite into the systemic circulation; V _m2 /M _am is about active metabolites released into the systemic circulation of drug clearance ratio of the apparent volume of distribution of the peripheral compartment of the metabolite; CL _m / m _am is metabolized into the active metabolite on drug metabolites metabolite fraction from the center Atrioventricular clearance; Q _m /M _am is the interventricular clearance or flux between metabolites at the central and peripheral compartments of the fraction of active drug metabolized to metabolites.

These parameters are similar to the V ₁ /F, V ₂ /F, CL/F, and Q/F parameters used to model data after oral administration of the drug when data after intravenous administration is not available.

Because it is not possible to get all the information you need in a single individual, a population modeling approach is used. In this manner, it is assumed that the parameters of each individual are derived from statistical distributions determined from data from a large group of individuals. The modeling approach then uses information from the individual's own dataset and from a broader population to estimate the most likely set of parameters for that individual, which can then be used to estimate all of the individuals in the dosing phase. The concentration of the relevant compound. As an example, if there is data on the active drug and the metabolite data and the metabolites in the population after administration of the active drug, and there are also data on the drug contained in the nanoparticle and the administration of the nanoparticle formulation The data for metabolites in an individual can be viewed as using the individual's own data to determine the pharmacokinetics of the drug both in the body and in the nanoparticle. This is then combined with the elimination rate of the drug from the nanoparticle and the rate of occurrence of the metabolite and the population data of the active drug to estimate the drug that is used both in the body and in the nanoparticle, the active drug that has been released in the body. And the most likely parameter set of metabolites in the individual.

The invention will now be further described with reference to the accompanying examples and drawings of the experimental model of the rat which describes the method of the invention. The skilled person will understand how to apply the following experiments (implemented in rats) to humans.

Figure 1 shows the observation of prodrugs in plasma samples produced in experimental rat models after active drug administration at 0 h, prodrug administration at 168 h, and active drug in 326 h of nanoparticle formulation. And predicted plasma concentration plots.

Figure 2 shows the observation of active drug in plasma samples produced in experimental rat models after active drug administration at 0 h, prodrug administration at 168 h, and active drug in 326 h of nanoparticle formulation. And predicted plasma concentration plots.

Figure 3 is a graph showing the plasma samples produced in the experimental rat model in the plasma samples after administration of the active drug at 0 h, the prodrug administration at 168 h, and the active drug in the 326 h of the nanoparticle formulation. A graph of observed and predicted plasma concentrations of active drugs.

Figure 4 is a graph showing the observation of metabolites in plasma samples produced in experimental rat models after active drug administration at 0 h, prodrug administration at 168 h, and active drug in 326 h of nanoparticle formulation. And predicted plasma concentration plots.

1 Overview of bioanalytical methods for measuring total drugs and metabolites from in vivo samples administered to nanoparticles

An exemplary method is provided below whereby a metabolite of AZD1152 hqpa loaded nanoparticles or a nanoparticle loaded with AZD1152 hqpa can be extracted from a sample and assayed, and the amount of AZD1152 hqpa or metabolite present is determined. . The method described is a multi-step process that should be performed on ice to prevent the spontaneous release of AZD1152 hqpa drug from the nanoparticle wherever possible.

1.1 Total drug extraction method:

• Dissolve the solid parent drug in DMSO to a concentration of 2 mM.

• A 50 [mu]l aliquot of each plasma sample was injected into a 96 well plate using the appropriate dilution factor.

• Prepare a standard calibration curve from a 2 mM stock solution in DMSO using a Hamilton Star Robot (see Appendix 1 for preparation details)

• Add 150 μl of acetonitrile with the internal standard.

• Shake the plate to mix the samples.

• Rotate in a centrifuge for 10 minutes at 4500 rpm.

• Transfer 50 μl of supernatant to a clean 96-well plate.

• Add 300 μl of water.

• Analysis via LCMSMS.

1.2 Metabolite extraction method:

• Dissolve the metabolite in DMSO to a concentration of 2 mM.

- A 12.5 [mu]l aliquot of each plasma sample was injected into a 96 well plate.

• Prepare a standard calibration curve from a 2 mM stock solution in DMSO using a Hamilton Star Robot (see Appendix 1 for preparation details)

• Add 37.5 μl of acetonitrile with the internal standard.

• Shake the plate to mix the samples.

• Rotate in a centrifuge for 10 minutes at 4500 rpm.

• Transfer 25 μl of supernatant to a clean 96-well plate.

• Add 150 μl of water.

• Analysis via LCMSMS.

2 standard curve making details

Generating a standard curve is useful in determining the amount of drug or metabolite present in a sample.

It is possible to synthesize the metabolite 2-(3-((7-(3-(ethyl(2-hydroxyethyl))amino)propoxy)quinazolin-4-yl)amino)-1H-pyrazole- 5-Base) Acetic Acid, also known as AZ12102238, is produced in an amount sufficient to rapidly produce a standard curve.

The starting material (2-(3-((7-(3-chloropropoxy)quinazolin-4-yl)amino)-1H-pyrazol-5-yl)acetic acid) has been described in the following literature : Mortlock et al., a selective inhibitor of Aurora B kinase, the discovery, synthesis, and in vivo activity of a new class of pyrazolylamine quinazolines (Discovery, Synthesis, and in Vivo Activity of a New Class of Pyrazolylamino Quinazolines as Selective Inhibitors of Aurora B Kinase); Journal of Medicinal Chemistry (2007), 50(9), 2213-2224.

The metabolite can be synthesized by adding 2-(ethylamino)ethanol (15.04 ml, 154.24 mmol) to 2-(3-((7)) in DMA (20 ml) at 90 ° C under nitrogen. -(3-Chloropropoxy)quinazolin-4-yl)amino)-1H-pyrazol-5-yl)acetic acid (5 g, 12.85 mmol). The resulting solution was stirred at 90 ° C for 12 hours. The reaction mixture was cooled to EtOAc EtOAc (EtOAc)EtOAc. The water was evaporated by lyophilization to give a yellow oil (11.3 g), mainly an excess of amine ethylethanol and the desired product.

Purification of 1 g batch by preparative HPLC (Waters SunFire column, 5 μm ceria, 50 mm diameter, 100 mm length) using a polar mixture of water (containing 0.1% TFA) and MeCN as eluent This product. The fractions containing the desired compound are evaporated to dryness to give 2-(3-((7-(3-(ethyl(2-hydroxyethyl))amino)propoxy)quinazoline as a pale yellow gum. 4-yl)amino)-1H-pyrazol-5-yl)acetic acid (0.418 g, 6.15%). 1H NMR (400MHz, DMSO, 30 ° C) 1.24 (3H, t), 2.12 - 2.28 (2H, m), 3.17-3.38 (6H, m), 3.68 (2H, s), 3.73-3.85 (2H, m) , 4.27 (2H, t), 6.66 (1H, s), 7.29-7.32 (1H, m), 7.33 (1H, d), 8.66 (1H, d), 8.75 (1H, s), 9.56 (1H, s ), 11.16 (1H, s). No 2x NH/OH was observed. Expected value of Hs: 26 assigned Hs: 24. m/z: ES+[M+]414

A slight change to this synthesis is given below: 2-(3-((7-(3-chloropropoxy)quinazolin-4-yl)amino)-1H in DMF (250.00 mL) 2-(Ethylamino)ethanol (46.56 g, 522.32 mmol) was added to a suspension of pyrazole-5-yl)acetic acid (26.00 g, 65.29 mmol). The yellow solution was then stirred at 90 ° C for 6 hours. The DMF was removed under reduced pressure using an oil pump. The product was purified by preparative HPLC (column: Phenomenex luna C18, 250 x 77 mm x 10 μm, using a decreasing polar mixture of water (containing 0.1% TFA) and MeCN as eluent. Most of the water was removed under vacuum. in H ₂ O (70mL) was added MeCN (200 mL), and then the mixture was stirred at 0 ℃ 1h. the resulting precipitate was filtered and washed with MeCN (100mL), then dried under vacuum was obtained as a pale yellow solid Product AZ12102238 (5.10 g, 12.23 mmol, 18.73% yield, 99.4% purity).

A standard curve can be generated by an automated device. Prior to serial dilution of the stock solution from right to left in the microplate, the automated machine will first add the appropriate diluent to the microplate for dilution, one for each compound (Table 1).

2.5 μl from column 1-11 was then placed from left to right into wells 2-12 of the matrix plate to generate an eleven point curve (Table 2).

Columns 1-11 from Table 1 were placed into columns 2-12 of the matrix plate to produce an eleven point calibration curve as above.

3 Evaluation of drugs loaded with nanoparticle or their metabolites

As mentioned above, LC-MS or MS methods can be used to assess the nanoparticles of the loaded drug or their metabolites and to determine the amount of such compounds present. By way of example, the following parameters listed in Tables 3 and 4 can be used in embodiments that utilize AZD1152 hqpa, or its metabolites of AZ12102238.

4 example model fitting

This example model fit was performed by administering a single intravenous bolus injection of the active drug AZD1152 hqpa at 0 h, a single intravenous bolus injection of the prodrug AZD 1152 at 168 h, and a single intravenous bolus injection of the nanoparticle formulation at 336 h. Active drug in rats. Plasma concentrations of active drugs and metabolites were measured at various time points after administration of AZD 1152 hqpa and until AZD 1152 was administered. Plasma concentrations of prodrugs, active drugs, and metabolites were measured at various time points after administration of the prodrug and until the administration of the nanoparticle formulation. After administration of the nanoparticle formulation, the plasma concentration of the active drug and the plasma concentration of the metabolite in the nanoparticles were measured at various time points.

These parameters are shown for individual rats, but these parameters are derived from a population pharmacokinetic model constructed using 3600 data points from 850 rats, for prodrugs, Each of the encapsulated active agents in the active drug, metabolite, and nanoparticle formulation is administered in a variety of dosage regimens.

4.1 Preparation of nanoparticle encapsulated drugs and comparator formulations

abbreviation:

The following abbrils can be used:

"Polymer PEG" refers to a PLA-PEG copolymer wherein the copolymer has a poly(lactic acid) having a number average molecular weight of about 16 kDa and a poly(ethylene) glycol having a number average molecular weight of about 5 kDa. Such polymers are commercially available or can be made by methods known in the art. Such polymers are used in the examples in WO 2010/005721.

4.2 Example of using a nominal 1g batch

AZD1152 hqpa nanoparticles having pumice acid were prepared with the compositions as listed in Table 5.

4.2.1 Preparation of the acid solution. By mixing 2.9 g of pamoate with 7.1 g in a container DMSO, a 29% (w/w) solution of chloric acid in DMSO was prepared. The vessel was heated in a heated oven at 70-80 ° C until all the acid was dissolved.

4.2.2 Preparation of 8% TFA/7.5% water/84.5% benzyl alcohol (wt%) solution. Trifluoroacetic acid (TFA) (3.2 g), deionized (DI) water (3.0 g), and benzyl alcohol (BA) (33.8 g) were combined to prepare 8% TFA / 7.5% water / 84.5% benzyl alcohol (wt%) solution.

4.2.3 Buffer preparation:

To make 1000 ml of 0.17 M phosphate (pKa2 = 7.2) buffer: pH = 6.5, prepare two stock buffers: A. 13.26 g of sodium dihydrogen phosphate, anhydrous NaH ₂ PO ₄ H ₂ O (Mr = 119.98 Dissolved in 650 ml of pure water, and B. Dissolved 10.82 g of disodium hydrogen phosphate and anhydrous NaH ₂ PO ₄ (Mr = 141.96) in 650 ml of pure water. Buffer B was added to Buffer A while mixing until pH = 6.50 at a laboratory temperature of 25 °C.

alternative plan:

To make 1000 ml of 0.17 M sodium phosphate buffer at pH 6.5: to approximately 800 ml of DI water, 16.26 g of sodium dihydrogen phosphate dihydrate (NaH ₂ PO ₄ -2H ₂ 0; FW = 156.01) and 11.70 g were dissolved. Disodium hydrogen phosphate dihydrate (Na ₂ HPO ₄ -2H ₂ 0; FW = 177.99), and adding enough additional amount of water to reach 1000 ml at a laboratory temperature of 25 °C.

4.2.4 Preparation of polymer solution

● Add polymer-PEG to a 20 mL glass vial, 591.3 mg

- Add 5978.6 mg of ethyl acetate to a glass vial and vortex overnight to give a polymer-EA solution.

4.2.5 Preparation of aqueous solution

● In water, 0.12% Brij® 100, 4% benzyl alcohol, 5.7% DMSO

• Add 1.4 g Brij® 100, and 901.6 g DI water to a 1 L bottle and mix on a stir plate until dissolved.

• Add 40 g of benzyl alcohol and 57 g of DMSO to Brij®/water and mix on a stir plate until dissolved.

4.2.6 Preparation of drug solution

● Weigh 253.4mg of AZD1152 hqpa in a 20ml scintillation vial

Add 2026.8 mg of the above 8% TFA/7.5% water/BA solution to AZD1152

- 535.5 mg of the above 29% pamoate/DMSO solution was added to the drug solution and vortexed to give a clear drug solution.

• Combine the drug solution and the polymer solution just prior to formulation.

4.2.7 Preparation of emulsion The ratio of aqueous phase to organic phase is 5.5:1

• The organic phase was poured into an aqueous solution at room temperature and homogenized using a hand-held rotor/stator homogenizer for 10 seconds to form a crude emulsion. Store in ice for 10-15 minutes.

• Set the feed solution carefully through a high pressure homogenizer (110S) at a pressure of approximately 9,000 psi on a compressed air inlet pressure gauge to form a nanoemulsion nanoparticle formulation.

• Pour the emulsion into a quenching solution (0.17 M sodium phosphate, pH 6.5) at <5 ° C while stirring on a stir plate. Make sure at least 5 minutes have elapsed since the start of collection before quenching. The ratio of quenching liquid to emulsion is 3:1 by weight.

• Add 35% (w/w) Tween® 80 to Tween® 80 and the drug at a ratio of 20:1 by weight for quenching.

• Concentration of nanoparticles by tangential flow filtration (TFF).

- Using a 300 kDa Pall box (3 x 0.1 ^m2 membrane), concentrate the quench on TFF to approximately 200 mL.

• Percolation of approximately 20 percolation volumes (4 liters) using ambient temperature DI water.

● Reduce the volume to the minimum volume

• Add 100 mL of DI water to the vessel and pump through the membrane for cleaning.

● Collect materials in glass vials (approximately 100 mL)

4.2.8 Determine the solids concentration of the unfiltered final slurry.

• Add one volume of the final slurry to a tared 20 mL scintillation vial and dry under vacuum on a Lyo/oven.

• Determine the weight of the nanoparticle in the dried slurry of this volume.

4.2.9 Determine the solids concentration of the final slurry filtered at 0.45 μm:

• A portion of the final slurry sample was filtered prior to the addition of sucrose through the 0.45 [mu]m syringe filter.

• Add one volume of filtered sample to a tared 20 mL scintillation vial and dry under vacuum on a Lyo/oven.

4.2.10 Add a portion of sucrose to the final 9 unfiltered slurry samples to achieve 10% sucrose by weight.

4.2.11 Free sample of the unfiltered final slurry with sucrose was frozen.

Alternative method for making formulation G1: (using a nominal 1g batch)

4.2a.1 Preparation of polymer solution

● Add polymer-PEG to a 20 mL glass vial, 700 mg

• Add 7078 mg of ethyl acetate to a glass vial and vortex overnight to give a polymer-EA solution.

4.2a.2 Preparation of aqueous solution

● In water, 0.12% Brij® 100, 4% benzyl alcohol

• Add 1.2 g Brij® 100, and 958.8 g DI water to a 1 L bottle and mix on a stir plate until dissolved.

• Add 40 g of benzyl alcohol to Brij®/water and mix on a stir plate until dissolved.

4.2a.3 Preparation of drug solution

● Weigh 300mg of AZD1152 hqpa in a 20ml scintillation vial

Add 2399mg of the above 8% TFA/7.5% water/BA solution to AZD1152

- 634 mg of the above 29% pamoate/DMSO solution was added to the drug solution and vortexed to give a clear drug solution.

• Combine the drug solution and the polymer solution just prior to formulation.

4.2a.4 Preparation of emulsion The ratio of aqueous phase to organic phase is 5:1

• The organic phase was poured into an aqueous solution at room temperature and homogenized using a hand-held rotor/stator homogenizer for 10 seconds to form a crude emulsion. Store in ice for 10-15 minutes.

• Set the feed solution carefully through a high pressure homogenizer (110S) at a pressure of approximately 9000 psi on a compressed air inlet pressure gauge to form a nanoemulsion

Preparation of nanoparticle

• Pour the emulsion into a quenching solution (0.17 M sodium phosphate, pH 6.5) at <5 ° C while stirring on a stir plate. Make sure at least 5 minutes have elapsed since the start of collection before quenching. The ratio of quenching liquid to emulsion is 10:1

• Add 35% (w/w) Tween® 80 to Tween® 80 and the drug at a ratio of 20:1 by weight for quenching.

• Concentration of nanoparticles by tangential flow filtration (TFF).

- Using a 300 kDa Pall box (3 x 0.1 ^m2 membrane), concentrate the quench on TFF to approximately 200 mL.

• Use cold DI water to diafilter approximately 20 percolation volumes (4 liters).

● Reduce the volume to the minimum volume

• Add 100 mL of cold water to the vessel and pump through the membrane for cleaning.

● Collect materials in glass vials (approximately 100 mL)

4.2a.5 Determine the solids concentration of the unfiltered final slurry.

• Add one volume of the final slurry to a tared 20 mL scintillation vial and dry under vacuum on a Lyo/oven.

Determine the weight of the nanoparticles in the dried slurry of this volume

4.2a.6 Determine the solids concentration of the final slurry filtered at 0.45 μm:

• A portion of the final slurry sample was filtered prior to the addition of sucrose through the 0.45 [mu]m syringe filter.

• Add one volume of filtered sample to a tared 20 mL scintillation vial and dry under vacuum on a Lyo/oven.

4.2a.7 Add a portion of sucrose to the final 9 samples of the slurry to achieve 10% sucrose.

4.2a.8 Free the remaining sample of the unfiltered final slurry with sucrose.

Another acid-promoting formulation, hereinafter referred to as Formulation G2, was prepared as follows, using a nominal 1 g batch and having the composition as shown in Table 5a:

Example 4.2b

4.2b.1 Preparation of the acid solution. A 29% (w/w) solution of pamoic acid in DMSO was prepared by mixing 2.9 g of pamoate with 7.1 g of DMSO in a container. The vessel was heated in a heated oven at 70-80 ° C until all the acid was dissolved.

4.2b.2 Preparation of 8% TFA/7.5% water/84.5% benzyl alcohol (wt%) solution. Trifluoroacetic acid (TFA) (3.2 g), deionized (DI) water (3.0 g), and benzyl alcohol (BA) (33.8 g) were combined to prepare 8% TFA / 7.5% water / 84.5% benzyl alcohol (wt%) solution.

4.2b.3 Buffer preparation:

To make 1000 ml of 0.17 M phosphate (pKa2 = 7.2) buffer: pH = 6.5, prepare two stock buffers: A. 13.26 g of sodium dihydrogen phosphate, anhydrous NaH ₂ PO ₄ H ₂ O (Mr = 119.98 Dissolved in 650 ml of pure water, and B. Dissolved 10.82 g of disodium hydrogen phosphate and anhydrous NaH ₂ PO ₄ (Mr = 141.96) in 650 ml of pure water. Buffer B was added to Buffer A while mixing until pH = 6.50 at a laboratory temperature of 25 °C.

alternative plan:

To make 1000 ml of 0.17 M sodium phosphate buffer at pH 6.5: to approximately 800 ml of DI water, 16.26 g of sodium dihydrogen phosphate dihydrate (NaH ₂ PO ₄ -2H ₂ 0; FW = 156.01) and 11.70 g were dissolved. Disodium hydrogen phosphate dihydrate (Na ₂ HPO ₄ -2H ₂ 0; FW = 177.99), and adding enough additional amount of water to reach 1000 ml at a laboratory temperature of 25 °C.

4.2b.4 Preparation of polymer solution

● Add polymer-PEG to a 20 mL glass vial, 700 mg

• Add 6572 mg of ethyl acetate to a glass vial and vortex overnight to give a polymer-EA solution.

4.2b.5 Preparation of aqueous solution

● In water, 0.15% Brij® 100, 4% benzyl alcohol

• Add 1.5 g Brij® 100, and 958.5 g DI water to a 1 L bottle and mix on a stir plate until dissolved.

• Add 40 g of benzyl alcohol to Brij®/water and mix on a stir plate until dissolved.

4.2b.6 Preparation of drug solution

● Weigh 300mg of AZD1152 hqpa in a 20ml scintillation vial

Add 2746 mg of the above 8% TFA/7.5% water/BA solution to AZD1152

- 792 mg of the above 29% pamoate/DMSO solution was added to the drug solution and vortexed to give a clear drug solution.

• Combine the drug solution and the polymer solution just prior to formulation.

4.2b.7 Preparation of emulsion The ratio of aqueous phase to organic phase is 5:1

• The organic phase was poured into an aqueous solution at room temperature and homogenized using a hand-held rotor/stator homogenizer for 10 seconds to form a crude emulsion. Store in ice for 10 minutes.

• Set the feed solution carefully through a high pressure homogenizer (110S) at a pressure of approximately 9000 psi on a compressed air inlet pressure gauge to form a nanoemulsion Preparation of nanoparticle

• Immediately at <5 ° C, pour the emulsion into a quenching solution (0.17 M sodium phosphate, pH 6.5) while stirring on a stir plate. The ratio of quenching liquid to emulsion is 10:1

• Add 35% (w/w) Tween® 80 to Tween® 80 and the drug at a ratio of 20:1 by weight for quenching.

• Concentration of nanoparticles by tangential flow filtration (TFF).

- Using a 300 kDa Pall box (3 x 0.1 ^m2 membrane), concentrate the quench on TFF to approximately 200 mL.

• Use cold DI water to diafilter approximately 20 percolation volumes (4 liters).

● Reduce the volume to the minimum volume

• Add 100 mL of cold water to the vessel and pump through the membrane for cleaning.

● Collect materials in glass vials (approximately 100 mL)

4.2b.8 Determine the solids concentration of the unfiltered final slurry.

• Add one volume of the final slurry to a tared 20 mL scintillation vial and dry under vacuum on a Lyo/oven.

Determine the weight of the nanoparticles in the dried slurry of this volume

4.2b.9 Determine the solids concentration of the final slurry filtered at 0.45 μm:

• A portion of the final slurry sample was filtered prior to the addition of sucrose through the 0.45 [mu]m syringe filter.

• Add one volume of filtered sample to a tared 20 mL scintillation vial and dry under vacuum on a Lyo/oven.

4.2b.10 Add a portion of sucrose to the final 9 parts of the slurry sample to achieve 10% sucrose by weight.

4.2b.11 Free the remaining sample of the unfiltered final slurry with sucrose.

4.3 Model equation

The model equations used in this example were previously described under the heading "Example Rat Model":

4.4 Model parameters:

The model parameters are listed in Table 6.

4.5 History of administration and observed and predicted concentrations

At the times listed in Table 7, rats were administered by intravenous bolus with the following compounds.

The observed and predicted concentrations for each of the prodrug, the active drug, the active drug contained within the nanoparticle, and the metabolite are shown in Table 8, and are illustrated in Figures 1-4.

The observed and predicted plasma concentrations of the prodrugs after administration of active drug at 0 h, prodrug administration at 168 h, and active drug in 336 h of nanoparticle formulation are shown in Figure 1.

The observed and predicted plasma concentrations of the active drug after administration of the active drug at 0 h, the prodrug administration at 168 h, and the active drug in the 336 h nanoparticle formulation are shown in Figure 2.

The observed and predicted plasma concentrations of the active drug in the nanoparticles after the active drug administration at 0 h, the prodrug administration at 168 h, and the active drug in the 336 h nanoparticle formulation are shown in Figure 3.

Metabolite observed and predicted plasma concentrations after active drug administration at 0 h, prodrug administration at 168 h, and active drug in 336 h of nanoparticle formulation are shown in Figure 4.

5 Discussion

In the above examples, it is assumed that the route of administration does not alter the pharmacokinetic behavior of the active drug (ie, such that the active drug administered by intravenous bolus is in the same manner as the drug formed from the prodrug or released from the nanoparticle formulation) effect). Similarly, it is hypothesized that the route of administration does not alter the pharmacokinetic behavior of the metabolite (ie, the metabolite formed from the active drug that has been administered by intravenous bolus is formed or formed from the active drug formed from the prodrug. The metabolite of the active drug released from the nanoparticle formulation acts in the same manner).

Due to the above assumptions, it is possible to describe the concentration time curve of the active drug after administration of the nanoparticles, without the measurement of the released active drug, as long as the input curve of the released active drug entering the body is known. The input curve is assumed to be from the first stage release of the active drug contained in the nanoparticle (i.e., the rate is proportional to the amount of active drug still in the nanoparticle).

Knowledge of the concentration time profile of the active drug still contained in the nanoparticle provides the input shape of the active drug, but this information does not by itself provide the extent of release from the nanoparticle formulation. The metabolite concentration time profile observed after administration of the nanoparticle formulation provides information on the extent to which the active drug is released from the nanoparticle, along with the extent to which metabolites are formed from the active drug. Since information on the extent of formation of metabolites from the active drug has been obtained from both the concentration time curves after administration of the active drug and the prodrug, it is possible to introduce the extent of release of the active drug from the nanoparticle formulation.

In the above example, information about the plasma concentration of the prodrug over time is not required (although it can provide useful information for the model). However, it is necessary to know how the plasma concentrations of active drugs and metabolites change after administration of the active drug. As discussed elsewhere in this specification, having information about how plasma concentrations change over time after administration of a metabolite can help to accurately determine the amount of systemically released active drug in a subject, but this is not necessary.

Information about the concentration of the drug in the nanoparticle is necessary to provide an input rate. The advantage system model that uses all other information in the population model to fit the data generated from the individual rat uses information from this individual along with a much larger data set from multiple individuals. In this example, it is not of utmost importance to have information from the entire population as information available to the active drug and nanoparticle formulation for use in this individual. That is, normally, only the rat nanoparticle formulation will be administered.

6 Summary of results

As can be seen from Figure 2, knowledge of the amount of metabolites of AZD1152 hqpa present in the sample over time allows for accurate derivation of the amount of AZD1152 hqpa that is systemically released in the subject. Therefore, although the concentration of the released active drug cannot be accurately measured (due to the potential of the nanoparticle to rupture or leak the drug during sample preparation or measurement), it can be based on knowledge of metabolite levels and the application of a suitable pharmacokinetic model, accurate This concentration is predicted. The predicted concentration of the released active drug can then be used to construct a pharmacokinetic-pharmacodynamic (pkpd) model to correlate the administration of the nanoparticle encapsulating drug with the resulting biological changes (eg, biomarker levels, or toxicity). Changes, or changes in tumor growth inhibition).

Compound A: 2-ethyl-4-{[2'-(1H-tetrazol-5-yl)biphenyl-4-yl]methoxy}quinoline (internal standard). See examples WO 92/02508 and WO 92/13853.

7. Alternative metabolite synthesis

AZD1152-hqpa N-oxide (N-ethyl-3-[4-[[3-[2-(3-fluoroanilino))-2-oxo-ethyl]-1H-pyridyl can be cleaved as follows Zyrid-5-yl]amino]quinazolin-7-yl]oxy-N-(2-hydroxyethyl)propan-1-amine oxide: to CH ₂ Cl ₂ (400.00 mL) m-CPBA (8.00 g, 39.40 mmol, 2.00 equiv, 85% w/w) was added to a suspension of AZD 1152 hqpa (10.00 g, 19.70 mmol, 1.00 equiv), then the yellow suspension was stirred at 0 ° C for 8 hours, yellow solid precipitation. The solid was filtered, then the solid was dried in vacuo and the CH ₂ Cl ₂ layer was washed with Na ₂ S ₂ O ₃ (10%, 300 mL*1) then washed with saturated brine (300 mL*1) with anhydrous Na ₂ SO ₄ dried, filtered, and concentrated in vacuo. By prep HPLC (TFA conditions and then basic conditions) The combined solid was purified to remove CH ₃ CN, and then dried by lyophilization in vacuo. The product AZD1152 hqpa N-oxide (1.70 g, 3.16 mmol, 16.05% yield, 97.4% purity) was obtained as a yellow solid.

LCMS: MS (ESI) m/z 524.2 [M+H]+

HPLC: 5.184 (purity: 97.40%)

¹ H NMR: (400 MHz, methanol-d ₄ ) δ=8.55 (br.s., 1H), 8.25 (d, J = 9.3 Hz, 1H), 7.57 (d, J = 11.5 Hz, 1H), 7.36~ 7.21(m,3H), 7.17(br.s.,1H), 6.86~6.79(m,1H), 4.27(t, J =5.5Hz,1H), 4.06~3.98(m,1H),3.79(br .s., 1H), 3.55 (dd, J = 5.5, 10.4 Hz, 1H), 3.50-3.39 (m, 2H), 2.36 (dd, J = 5.5, 10.4 Hz, 2H), 1.36 (t, J = 7.1 Hz, 3H).

Reference example: Draft FDA guidelines for doxorubicin ( recommended in February 2010; November 2013, revised December 2014)

Active ingredient: doxorubicin hydrochloride

Dosage form; route: liposome injection; intravenous

Recommended study: two studies

When tested and referenced PEGylated liposome products

Having the same pharmaceutical product composition and ● is produced by an active liposome loading process with an ammonium sulfate gradient, and • Equivalent liposome characteristics, including liposome composition, encapsulated drug status, liposome environment, liposome size distribution, thin layer number, grafted PEG on the surface of liposomes, electrical surface potential or charge, and extracorporeal leakage Rate time.

The following clinical and in vitro studies are recommended to demonstrate bioequivalence:

In vivo bioequivalence studies:

1. Type of study: fasting*

Design: single dose in vivo, two-way crossover experiment

Strength: 50mg / vial or 20mg / vial

Dosage: 50mg/m ²

Subject: Ovarian cancer patients whose disease has progressed or relapsed after platinum-based chemotherapy and have been received or planned to begin treatment with a reference list drug (RLD) or a reference standard product.

Additional comments:

● Adriamycin-based cytotoxic drugs. Therefore, Bio-IND is required for bioequivalence studies of doxorubicin liposome injection to ensure the safety of human test subjects.

• When the patient plans to receive their usual treatment, the two arm systems of the crossover study were performed on two days of the day so that the treatment regimen was not altered or delayed.

• The criteria for a health care regimen should not be changed except that on the day of the indicated dosing, the patient is randomized to a test treatment or a reference treatment.

• In the case of a dose system every 4 weeks, two consecutive treatment cycles should be used for both treatment periods.

• In the two study periods, any accompanying medication must be strictly the same.

• Due to concerns about cardiotoxicity, documented cardiac conditions at baseline.

● Must be interrupted from the study and excluded from the analysis during the study period Any patient who requires ±5% dose adjustment.

Exclusion criteria:

• After four treatment cycles, it will result in a total lifetime exposure of 550 mg/m ² or more.

• The protocol must exclude patients with significantly impaired liver function in their exclusion criteria.

• Patients with a history of hypersensitivity to conventional formulations of doxorubicin HCl or components of RLD or reference standards should not enter the study.

● Women should not be pregnant or lactating.

● The patient is <18 years old or >75 years old.

● If it is treated with a myelotoxic drug, it is actively opportunistically infected by mycobacteria, cytomegalovirus, Toxoplasma, Pneumocystis carinii or other microorganisms.

● Clinically significant disease of the heart, liver, or kidney.

* If the patient's health condition prevents fasting, the sponsor can provide a non-high fat diet during the proposed study period. Alternatively, treatment can be initiated 2 hours after a standard (non-high fat) breakfast.

Analyte to be measured (in a suitable biological fluid): free doxorubicin and liposomal encapsulated doxorubicin.

Bioequivalence based on (90% CI) : AUC and Cmax for doxorubicin encapsulated with free doxorubicin and liposomes.

Note: Critical bioequivalence studies should be performed using test products produced by the proposed commercial scale manufacturing process.

In vitro studies:

2. Type of study: liposome size distribution

Design: in vitro bioequivalence study of at least three batches of tested and referenced products

Parameters to be measured: D10, D50, D90

Bioequivalence based on (95% confidence upper bound): using population bioequivalence methods, D50 and SPAN [(ie D90-D10)/D50] or polydispersity index.

Dissolution test method and sampling time: Dissolution information for this drug product can be found on the publicly available FDA recommended dissolution method website at http://www.accessdata.fda.gov/scripts/cder/dissolution/ publicly available. A comparative dissolution test was performed on 12 dosage units for each of all the strengths of the tested and referenced products. The specifications will be determined at the time of reviewing the abbreviated new drug application.

Additional information: Same drug product composition

As a parenteral drug product, the general doxorubicin HCl liposome injection must be qualitatively and quantitatively identical to the RLD or reference standard, except for differences in buffers, preservatives and antioxidants, the conditions of which The differences were identified and characterized, and it was demonstrated that these differences did not affect the safety/efficacy characteristics of the drug product. Currently, the FDA does not recommend a type of study that requires proof that the differences in buffers, preservatives, and antioxidants do not affect the safety/efficacy characteristics of the drug product.

Lipid excipients are critical in liposome formulations. The ANDA sponsor should obtain lipids from the same class of synthetic pathways (natural or synthetic) as found in RLD or reference standards. Information should be provided with chemical manufacturing and control involve a lipid component for the same level of detail in a drug substance is expected to draft guidelines for liposomal drug product in ¹ suggested in. The ANDA sponsor should have specifications for lipid excipients similar to those used to produce RLD or reference standards. Additional comparative characterization of lipid excipients including distribution of molecular species should be provided (beyond meeting specifications).

Active liposome loading process with ammonium sulfate gradient

In order to meet compositional equivalence and other equivalence tests, the ANDA sponsor is expected to use an active loading process with an ammonium sulfate gradient. The main steps include 1) formation of liposomes containing ammonium sulfate, 2) reduction in liposome size, 3) production of ammonium sulfate gradient, and 4) active drug loading. The active loading process uses a gradient of ammonium sulfate concentration between the internal and external environment of the liposome to drive the diffusion of doxorubicin into the liposomes ^2,3 .

Sponsors should use the quality of the design methodology to identify key material properties and key process parameters and guide process optimization. It is recommended to identify key process parameters and key material properties by assessing the sensitivity of liposome characteristics to changes in process parameters and attributes. The optimal value of the key process parameters should be selected based on the comparison of the resulting liposome characteristics with those of the RLD or reference standard.

Equivalent liposome characteristics

Use at least three batches of ANDA and RLD or reference standard products with other topical products with complex bioequivalence requirements (eg nasal spray and inhalation products) (at least one ANDA batch should be processed by commercial scale In vitro liposome characterization was performed and was used in in vivo bioequivalence studies. Attributes in the characterization of multiple ANDAs that require equivalent to RLD or reference standards should be included:

Liposomal composition: Liposomal compositions including lipid content, free and encapsulated drugs, internal and total sulfate and ammonium concentrations, histidine concentration, and sucrose concentration should be measured. The drug lipid ratio and the percentage of drug encapsulation can be calculated from the liposome composition values.

The state of the encapsulated drug: The doxorubicin in the RLD or reference standard is mostly in the form of doxorubicin sulfate precipitate in the liposome. In general, doxorubicin HCl liposomes must contain an equivalent of the doxorubicin precipitate in the liposome.

• Internal environment (volume, pH, sulfate and ammonium ion concentration): the internal environment of the liposome (including its volume, pH, sulfate and ammonium concentrations, maintenance of precipitated doxorubicin. Groups described in the liposome component) Measurement of the total and free concentrations of the fractions (including sulfate ions) allows for the inference of internal concentrations within the liposomes.

Liposomal morphology and thin layer number: Liposomal morphology and thin layer should be determined as drug loading, drug retention, and the rate at which drugs are released from the liposome. The effect of the extent of the thin layer.

• Lipid bilayer phase transition: Equivalence in lipid bilayer phase transitions will help to demonstrate equivalence in two-layer flow and consistency. The phase transition curves of the crude lipid excipients and liposomes should be comparable to those of the RLD or reference standards.

Liposomal size distribution: Liposomal size distribution is critical to ensure equivalent passive targeting. The ANDA sponsor should select the most appropriate particle size analysis method to determine the particle size distribution of both the tested and referenced products. For each tested and referenced product, the number of vials of liposome product to be studied should be no less than 30 (ie no less than 10 from each of the three batches). For details of the recommended statistical equivalence test, see Recommended Study 2 (above).

● Grafted PEG on the surface of liposomes: Surface-bound methoxypolyethylene glycol (MPEG) polymer coating protects liposomes from being removed by the mononuclear macrophage system (MPS) and increases blood circulation time . The thickness of the PEG layer is known to be thermodynamically limited and is estimated to be on the order of a few nanometers. The thickness of the PEG layer should be determined.

Electrical surface potential or charge: The surface charge on the liposome affects clearance, tissue distribution, and cellular uptake. The surface charge of the liposome should be measured.

• In vitro leakage under a variety of conditions: In vitro drug leak testing to characterize the physical state of the lipid bilayer and encapsulated doxorubicin should be investigated to support the loss of uncontrolled leakage under a range of physiological conditions and Equivalent delivery of tumor cells. The following are some examples of the proposed conditions.

Equivalent in vivo plasma pharmacokinetics of free and encapsulated drugs

Bio-IND is required for bioequivalence studies of doxorubicin liposomal injections in humans because of the doxorubicin-based cytotoxic drugs. We recommend a two-way cross-biological bioequivalence study in a single-dose fasting dose of 50 mg/m ^{2 in} patients with ovarian cancer. The sponsor should measure both liposome encapsulated and free doxorubicin to demonstrate that the general liposome formulation has the same in vivo stability as the .RLD or reference standard. These studies can be performed under fasted or standard dietary conditions depending on the needs of the patient. For details of the recommended statistical equivalence test, see Recommended Study 1 (above).

¹ Draft guiding principles for industry: chemistry, manufacturing, and control of lipopharmaceutical products; human pharmacokinetics and bioavailability; and labeling documents, FDA (2002), ² A. Gabyon (A.Gabizon) , H. Sheemda, Y. Barenholz. Pharmacokinetics of PEGylated liposomal doxorubicin: a review of animal and human studies (Pharmacokinetics of pegylated liposome doxorubicin: review of animal and Human studies). Clin Pharmcokinet 42(5): 419-436 (2003)

³ F. Martin. Product evolution and influence of formulation on pharmaceutical properties and pharmacology, Advisory Committee for Pharmaceutical Science Presentation (July 2001), http://www.fda.gov/ohrms/dockets/AC/01/slides/3763s2_08_martin.ppt. provides the following additional aspects:

CLAIMS 1. A method of measuring the amount of AZD1152 hqpa that is systemically released in a subject after administration of a nanoparticle comprising AZD1152 hqpa, the method comprising: determining a sample from the subject to determine The amount of metabolite of AZD1152 hqpa present in the sample; and • based on the determined amount of the metabolite, a pharmacokinetic model is applied to derive the amount of AZD1152 hqpa that is systemically released in the subject.

2. A method for determining a release profile of a nanoparticle loaded with AZD1152 hqpa in a biological system having the ability to metabolize the AZD1152 hqpa, the method comprising: • determining a sample from the biological system at a first time point, Determining a first amount of metabolites of such nanoparticles loaded with AZD1152 hqpa present in the sample; • at a second time point, the sample from the biological system is determined to determine a second amount of the metabolite of the nanoparticle loaded with the AZD1152 hqpa present in the sample; • based on the determined first amount and Two quantities, applying a pharmacokinetic model to derive a first value representative of the amount of nanoparticle of the load AZD1152 hqpa released at the first time point, and representing the load AZD1152 released at the second time point a second value of the amount of nanoparticle of hqpa; and • the first value and the second value are used to produce a release profile of the nanoparticle of the load AZD1152 hqpa.

3. A method of assessing the bioequivalence of a nanoparticle loaded with AZD1152 hqpa administered to a subject, the method comprising: - determining a sample from the subject to determine the presence of the sample in the sample The amount of the metabolite of the nanoparticle loaded with AZD1152 hqpa; ● based on the determined amount of the metabolite, applying a pharmacokinetic model to derive the systemically released AZD1152 hqpa nai of the subject in vivo The amount of rice granules; and • the value based on the amount of the nanoparticle loaded with such a load AZD1152 hqpa which is systemically released in the subject and the comparison value with respect to the second drug, and thereby evaluating the load AZD1152 hqpa The bioequivalence of the nanoparticle and the second drug.

The method of any one of aspects 1 to 3, wherein the metabolite is selected from the group consisting of AZD1152 hqpa defluoroaniline (also known as AZ12102238); AZD1152 hqpa defluoroaniline N - acetic acid; AZD1152 hqpa N-acetic acid; AZD1152 hqpa N-oxide; and AZD1152 hqpa N-deethyl.

5. The method of aspect 4, wherein the metabolite is AZ12102238.

6. The method of any of the above aspects, wherein the nanoparticle is selected from the group consisting of Materials of the following groups: diblock poly(lactic) acid-poly(ethylene) glycol copolymer; and diblock poly(lactic-glycolic acid copolymer)-poly(ethylene) glycol copolymer .

7. The method of any of the preceding aspects, wherein the AZD1152 hqpa is combined with a substantially hydrophobic acid within the nanoparticles.

8. The method of aspect 7, wherein the hydrophobic acid is selected from the group consisting of: deoxycholic acid; cholic acid; dioctyl sulfosuccinic acid; oleic acid;

9. The method of any of the preceding aspects, wherein the subject is a human.

10. The method of aspect 9, wherein the subject is involved in an individual investigating the characteristics of such a nanoparticle loaded with AZD1152 hqpa, such as a clinical trial of bioavailability.

The method of aspect 9 or aspect 10, wherein the subject has experienced an individual treated with such a nanoparticle loaded with AZD1152 hqpa.

The method of any of aspects 1 to 8, wherein the subject is a non-human animal.

13. The method of aspect 12, wherein the subject is for use in an animal in a preclinical investigation of such nanoparticles loaded with AZD1152 hqpa.

The method of aspect 12 or aspect 13, wherein the subject is a rat.

15. The method of any of the above aspects, wherein the sample is selected from the group consisting of: a tissue sample; and a body fluid sample.

16. The method of aspect 17, wherein the body fluid sample is selected from the group consisting of: a blood sample; a serum sample; a plasma sample; a urine sample; a lymph fluid sample; a tissue interstitial fluid sample; a bile sample; Sample; and stool sample.

17. The method of any of the preceding aspects, wherein the assay for the sample for the metabolite uses liquid chromatography-mass spectrometry.

18. The method of any of the preceding aspects, wherein the assay performed on the sample for the metabolite uses mass spectrometry imaging techniques.

19. The method of any of the preceding aspects, further comprising the step of determining a sample from the subject to determine the amount of nanoparticle loaded with AZD1152 hqpa in the sample.

20. The method of aspect 19, comprising measuring one or more additional samples from the subject and thereby deriving the amount of nanoparticle loaded AZD1152 hqpa present in the additional samples Another step.

The method of any one of aspects 3 to 20, wherein the curve is made with respect to the amount of such a nanoparticle loaded with AZD1152 hqpa that is systemically released over time in the subject.

22. The method of aspect 21, wherein the curve is a concentration curve.

23. The method of aspect 22, wherein the value of the amount of nanoparticle of the load AZD1152 hqpa for comparison with a comparative value relating to the second drug is selected from the group consisting of: Area (AUC); peak concentration ( _Cmax ); and peak concentration time ( _Tmax ).