Chem. Res. Toxicol. 2010, 23, 1871–1873
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Determination of Exposure Multiples of Human Metabolites for MIST Assessment in Preclinical Safety Species without Using Reference Standards or Radiolabeled Compounds Shuguang Ma, Zhiling Li, Keun-Joong Lee, and Swapan K. Chowdhury* Drug Metabolism and Pharmacokinetics, Merck Research Laboratories, 2015 Galloping Hill Road, Kenilworth, New Jersey 07033, United States ReceiVed October 27, 2010
A simple, reliable, and accurate method was developed for quantitative assessment of metabolite coverage in preclinical safety species by mixing equal volumes of human plasma with blank plasma of animal species and vice versa followed by an analysis using high-resolution full-scan accurate mass spectrometry. This approach provided comparable results (within (15%) to those obtained from regulated bioanalysis and did not require synthetic standards or radiolabeled compounds. In addition, both qualitative and quantitative data were obtained from a single LC-MS analysis on all metabolites and, therefore, the coverage of any metabolite of interest can be obtained. The U.S. Food and Drug Administration (FDA) (1) and International Conference on Harmonisation (ICH) (2) each issued a formal guidance on metabolites in safety testing (MIST) in February 2008 and June 2009, respectively. Metabolites identified only in human plasma or metabolites present at disproportionately higher levels in humans than in any of the animal test species should be considered for safety assessment. The metabolite level that triggers an assessment for nonclinical safety testing has been defined as 10% of the parent drug’s exposure at the steady state (FDA) or 10% of total drug-related exposure (ICH). Therefore, the identification of qualitative and quantitative differences in drug metabolism between animals used in nonclinical safety assessment and humans as early as possible is critical to avoid a delay of the drug development process (3, 4). Traditionally, the human metabolites are identified and quantified in a single-dose study with a radiolabeled drug (14C-AME) during phase II clinical development or after proofof-concept is achieved. The information generated from human AME study is not adequate to assess metabolism at steady state and may be too late for timely initiation of a large-scale clinical trial, if any human metabolite requires safety evaluation. Therefore, the processes and strategies generally used for generating human metabolism data to comply with the requirements of safety testing need a thorough evaluation in light of the new guidance (1, 2). One of the most appealing alternative approaches to adequately comply with the requirements of the guidance is to assess metabolism in the rising multiple-dose studies in humans, which are conducted early in the drug development program. Plasma samples from these studies can be used for metabolite identification and quantification at steady state, thus identifying if any human metabolite exceeds 10% of the total drug-related material and if those metabolites have been adequately tested in safety assessment. This is a very costeffective means to identify potential MIST-triggering metabolites early in clinical development programs. The “Hamilton” pooling approach, in which appropriate aliquots of the plasma samples obtained from different phar* Author to whom correspondence should be addressed (e-mail
[email protected].
macokinetic time points are pooled, yields one sample having a concentration of drug and metabolites proportional to the area under the curve (AUC) and that, therefore, can be used to assess the systemic exposure of the metabolites relative to that of the parent drug (5). Metabolism often results in structural changes that may change mass spectrometric responses of metabolites. Therefore, it remains considerably challenging to obtain quantitative metabolite profiles from nonradiolabeled first-in-human studies. A mass spectrometry (MS) response factor (RF) of each metabolite of interest relative to that of the parent drug is needed to semiquantify the metabolite level in biological matrices. Various methods have been developed for the determination of the metabolite’s response factor (6), which include (i) spiking metabolite reference standard and parent drug into plasma and measuring the peak area ratio from an LC-MS experiment (7); (ii) generating radiolabeled metabolites in animals or in vitro microsomal or hepatocytes incubations and determining the ratio of the MS responses to the corresponding radioactivity responses (8); and (iii) isolating metabolites and generating a calibration curve using 1H NMR or LC-MS (9, 10). Nevertheless, generating a MS RF is a very labor intensive process and, in some cases, impossible for every metabolite of interest. Using the approach described above, the animal-to-human exposure multiples of metabolites can be calculated as
EM )
(Ama /Apa) × RFma × AUCpa (Amh /Aph) × RFmh × AUCph
(1)
p where Am a is the peak area of metabolite in animal, Aa is the is the MS response factor peak area of parent in animal, RFm a of metabolite in animal, AUCpa is the parent AUC in animal, Ahm is the peak area of metabolite in human, Ahp is the peak area of parent in human, RFmh is the MS response factor of metabolite in human, and AUChp is the parent AUC in human. The regulatory guidance, however, does not require the knowledge of the actual concentrations of circulating metabolites as long as metabolites are adequately exposed in any one of the preclinical safety species. Recently, Gao et al. developed a method that eliminated the need for response correction in the
10.1021/tx100363k 2010 American Chemical Society Published on Web 12/01/2010
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Chem. Res. Toxicol., Vol. 23, No. 12, 2010
Ma et al.
Table 1. Peak Area Ratios of SCH-A and Its Metabolites (M5, M15, and M18) over Internal Standard in Rabbit and Human Plasma at the Steady State and Rabbit-to-Human Exposure Multiples Obtained from Full-Scan LC-HRMS rabbit (30 mg/kg) peak area ratio M5/IS M15/IS M18/IS parent/IS EM rabbit/human, rabbit/human, rabbit/human, rabbit/human,
rabbit (100 mg/kg)
rabbit (300 mg/kg)
human (100 mg)
mean (n ) 3)
% CV
mean (n ) 3)
% CV
mean (n ) 3)
% CV
mean (n ) 3)
% CV
0.0394 0.618 0.255 1.95
3.95 3.32 5.58 2.12
0.104 1.12 1.13 5.17
8.54 3.30 3.22 0.896
0.243 1.62 1.51 9.22
6.34 1.18 3.73 1.23
0.0197 0.0628 0.0943 0.811
5.53 2.93 2.97 1.99
2.70 (2.55)a 2.41 (2.39)b 2.01 9.84
M18 parent M5 M15
12.0 (12.4)a 6.37 (6.94)b 5.29 17.9
16.0 (16.6)a 11.4 (11.8)b 12.4 25.8
a The EM in parentheses was calculated from the ratio of AUC (M18) in rabbit over that in human using a validated bioanalytical method. b The EM in parentheses was calculated from the ratio of AUC (parent) in rabbit over that in human using a validated bioanalytical method.
assessment of exposure multiples of metabolites in preclinical species (11). This was accomplished by mixing equal volume of dosed human plasma with blank animal plasma and vice versa, followed by analysis of the plasma extracts by LC-MS/ MS. Gao et al. have demonstrated that semiquantitative comparison of metabolites in animals vs humans can be obtained from the peak area ratios of the metabolites vs internal standard from multiple reaction monitoring (MRM) experiments (11). Since both plasma samples are essentially identical (50:50, human:animal), the matrix difference across species was eliminated and the ratio of response factors becomes 1. Thus, the exposure multiple calculations can be simplified as:
EM )
(Ama /Apa) × AUCpa (Amh /Aph) × AUCph
(2)
With Hamilton pooling (5) and peak area normalization to an internal standard (IS)
AUCpa AUCph
)
(Apa /AISa ) (Aph/AISh )
(3)
IS where AIS a and Ah are the peak area of the internal standard in animal and human, respectively. Therefore, the equation can be further simplified to
EM )
(Ama /AISa ) (Amh /AISh )
(4)
This paper describes the determination of exposure multiples of human metabolites in preclinical safety species from the peak area ratio using the Gao et al. approach, but obtained from fullscan high-resolution mass spectrometry (HRMS) for two development programs, SCH-A and SCH-B, without using reference standards or radiolabeled compounds. The advantage of the current approach over that of Gao et al. is that a single analytical method is employed for both metabolite profiling and quantitative assessment of the coverage of all detectable metabolites in preclinical species without preselection of metabolites for MRM. All LC-MS experiments were performed on an Accela HPLC system (Thermo Fisher Scientific Inc., San Jose, CA) coupled with an LTQ-orbitrap mass spectrometer (Thermo Fisher Scientific Inc.). Experimental details consisting of the reagent used, sample preparation procedures, and HPLC and MS operation conditions can be found in the Supporting Information.
A schematic diagram for work procedures and proposed decision tree is also included in the Supporting Information. An oxidative deamination metabolite (M18) was identified as the most prominent circulating metabolite of SCH-A from 14 C-ADME studies in preclinical species. Other major metabolites included an N-dealkylation metabolite (M5) and an oxidative metabolite (M15). These metabolites also appeared to be major circulating metabolites in humans at the steady state without MS response correction. To assess the coverage of these metabolites in preclinical safety species, human plasma obtained from a rising multiple-dose study in healthy volunteers was pooled using the Hamilton pooling approach (5), mixed (1:1) with blank rabbit plasma, and profiled using LC-MS. Plasma from a repeated-dose toxicology study in female rabbits was similarly pooled, mixed (1:1) with blank human plasma, and profiled. An extracted ion chromatogram using a mass window of 5 ppm of each ion of interest was generated, and the peak area of the ion chromatogram was used for quantitation. Table 1 summarizes the peak area ratios of SCH-A and its metabolites (M5, M15, and M18) over internal standard in rabbit and human plasma determined from full-scan LC-MS measurements. Rabbit-to-human exposure multiples are calculated on the basis of eq 4 above. The exposure multiples of the parent drug, SCHA, were determined to be 2.41, 6.37, and 11.4 in rabbits after repeated doses of 30, 100, and 300 mg/kg, respectively. Similarly, the exposure multiples of M18 were determined to be 2.70, 12.0, and 16.0, respectively. SCH-A and M18 were also measured by a validated LC-MS/MS method, prior to the current study, which allowed us to calculate the exposure multiples using data from regulated bioanalysis and to compare the results with those obtained in the current study. The calculated exposure multiples for SCH-A from validated LCMS/MS measurements were 2.39, 6.94, and 11.8 in rabbits after repeated doses of 30, 100, and 300 mg/kg, respectively. The exposure multiples of SCH-A determined from the current study are in good agreement (within (10%) with those obtained from validated bioanalysis. The calculated exposure multiples for M18 were 2.55, 12.4, and 16.6, respectively, which are also in excellent agreement (within (6%) with those from the current study. The coverage of M5 and M15 was also assessed, and both were found to be adequately exposed to rabbits after repeated doses at all three dose levels (Table 1), even though these metabolites were not measured with a validated bioanalytical method. The approach was further validated from another development program, SCH-B, in which the parent and its oxidative metabolite (M7) were measured by a validated LC-MS/MS method in a rising multiple-dose study in healthy volunteers
Rapid Report
Chem. Res. Toxicol., Vol. 23, No. 12, 2010 1873
Table 2. Peak Area Ratios of SCH-B and Its Oxidative Metabolite (M7) over the Internal Standard in Dog and Human Plasma at the Steady-State and the Dog-to-Human Exposure Multiples Obtained from Full-Scan LC-HRMS dog (10 mg/kg) peak area ratio M7/IS parent/IS EM dog/human, M7 dog/human, parent
dog (20 mg/kg)
human (100 mg)
mean (n ) 3)
% CV
mean (n ) 3)
% CV
mean (n ) 3)
% CV
0.0847 5.18
1.15 0.29
0.304 11.7
3.43 3.18
0.127 0.824
11.2 8.63
0.671 (0.703)a 6.29 (6.91)b
2.41 (2.36)a 14.2 (16.4)b
a The EM number in parentheses was calculated from the ratio of AUC (M7) in dog over that in human using a validated bioanalytical method. b The EM in parentheses was calculated from the ratio of AUC (parent) in dog over that in human using a validated bioanalytical method.
and in a repeated-dose toxicology study in dogs. As shown in Table 2, M7 was adequately exposed in dogs (EM ) 2.41) following repeated doses of 20 mg/kg. The exposure multiples of the parent and M7 determined from the current study were all in good agreement (within (15%, Table 2) with those obtained from validated bioanalytical measurements. With 10 determinations in triplicates from two programs reported here, the exposure multiples of the parent and its metabolites determined from this study are all within (15% of those obtained from validated LC-MS/MS measurements. The results from this investigation thus clearly demonstrated that reliable quantitative assessment of metabolite coverage in safety species could be obtained in the absence of synthetic standards, radiolabeled compounds, or validated bioanalytical methods. However, precaution should be taken for analyzing “banked” plasma samples from toxicology studies if the stability of the metabolites is unknown. For metabolites known to have stability issues (e.g., acyl glucuronides), appropriate stabilization procedures (e.g., acidification) need to be implemented during plasma sample collection. In addition, the potential for injection carry-over should be evaluated. The method described here is similar in concept to that reported by Gao et al. HRMS is necessary for quantitation using full-scan LC-MS data because HRMS provides the selectivity for extracting analyte ions in the presence of isobaric interference ions in biological matrices. The main advantage of using fullscan HRMS for quantitation versus the MRM approach by Gao et al. is that the mass spectral information on all metabolites in a sample is collected. The acquired data set can be analyzed for quantitative assessment for any metabolite of interest, at any time during the development of a compound. A single method is used for both qualitative metabolite identification and quantitative metabolite coverage assessment. Moreover, no optimization in selecting the appropriate product ion or collision energy as required for MRM assays for prior-determined metabolites of interest is needed for full-scan HRMS analysis. Even though the linearity of the MS responses and assay sensitivity were not investigated in the current study, several recent papers have shown that comparable results were achieved in full-scan HRMS as obtained in the conventional tandem MS approach (12, 13). In conclusion, we describe a simple method for the determination of MIST coverage of drug metabolites. Utilizing accurate mass full-scan LC-MS analysis, both metabolite identification and reliable quantitative assessment of metabolite coverage in safety species could be obtained. In addition, the LC-MS data on all metabolites is captured in the full-scan LCMS analysis; therefore, this approach is applicable to the assessment of the coverage of any metabolite of interest. Furthermore, the method eliminates the need for a determination
if a metabolite is >10% of total drug-related material because assessment of the coverage of all detectable metabolites can be obtained from a single full-scan LC-HRMS analysis of plasma samples from humans and preclinical species. Supporting Information Available: Experimental materials and methods, and a schematic diagram for work procedures and proposed decision tree. This material is available free of charge via the Internet at http://pubs.acs.org.
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TX100363K
