CORRESPONDENCE
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© 2016 Nature America, Inc. All rights reserved.
Precision and robustness of 2D-NMR for structure assessment of filgrastim biosimilars To the Editor: With the advent of biosimilar versions of brand biologics, regulatory authorities in all major jurisdictions throughout the world have developed guidance documents to facilitate their approval1–4. The common theme in the new documents is the stipulation that sponsors must demonstrate biosimilarity between their proposed product and an approved reference product using state-of-the-art analytical technologies. In the US guidance documents, a “totality of evidence” approach is described that can be used to establish the degree of similarity and guide regulatory decision-making3,4. Higher-order structure is an important quality attribute of biosimilars that must be assessed by comparison to the reference licensed drug. To date, higher-order structure has been evaluated with low-resolution techniques, such as circular dichroism, Fourier transform infrared and Raman spectroscopies, and indirectly with several biological and stability assays5. In 2008, a two-dimensional nuclear magnetic resonance (2D-NMR) spectroscopy approach was first applied to the high-resolution assessment of the higher-order structure of a native recombinant protein therapeutic6. The technique resolves, in a 2D frequency map, the positions of proton–nitrogen atom pairs from each amide and amino group in a biologic molecule. Each signal correlates to the specific local chemical and structural environment of the atom pair; thus, the entire spectrum provides a comprehensive readout of the drug substance conformation along the polypeptide chain at atomic resolution, providing a potentially useful tool to establish drug substance consistency across manufacturing changes or comparability of the higher-order structure of biosimilars. In this work, an interlaboratory comparative study was performed on filgrastim (methionyl granulocyte colony-stimulating factor; Met-G-CSF) to demonstrate the precision and robustness of the 2D-NMR approach. Filgrastim was selected because of its therapeutic importance, because the drug had been characterized by NMR7 and because a number of filgrastim biosimilars have already been approved in Europe, the United States and other jurisdictions. Here, a USapproved originator product (Neupogen) and three unapproved, non-US-sourced
filgrastim products were used in their fully formulated states (Supplementary Table 1) to prepare a set of four samples for analysis using heteronuclear 2D-NMR correlation at 15N natural isotopic abundance. Spectra were acquired on the same samples on six different spectrometers, at four different field strengths ranging from 500 MHz to 900 MHz, in four different laboratories (for instrument specifications and experimental parameters, see Supplementary Tables 2–9). All the NMR data were analyzed and evaluated using the same software packages for visual evaluation, chemical shift analysis and principal-component analysis (PCA) to assess spectral similarity through multiple approaches. The interlaboratory study data show that the resolution of the NMR method allows one to quickly visualize the high degree of similarity of the spectral patterns obtained from the 2D-NMR experiments run on different spectrometers. In this respect, visual comparison of spectral overlays allows an operator to directly assess sample similarity (Fig. 1a, Supplementary Table 10 and Supplementary Figs. 1–4). Differences between two spectral patterns can result from variation in solution conditions (such as pH or ionic strength), variation in the temperature of the sample, and/or differences in the higher-order structure of the protein. As an example, in our study, the overlay of spectra acquired for the same filgrastim sample on two spectrometers revealed a number of peak signal deviations that could be mapped to solvent-exposed residues (Fig. 1a, inset). Four representative residues in loop regions that exhibited these deviations are shown in Supplementary Figure 2b. We found that these differences could be explained by differences in temperature of 2 °C and 4 °C for the HC 700 and HC 600 spectrometers, respectively. The change of temperature does not affect all amide resonances equally7 and has been described by Baxter and Williamson8. Proper instrument calibration removed these discrepancies (Supplementary Fig. 2c). For a more quantitative analysis, chemical shifts of each individual signal in the 2D map were compared using a root mean square deviation (RMSD) analysis or combined chemical shift difference (CCSD) methods (Fig. 1b,c, Supplementary Figs. 5 and 6,
NATURE BIOTECHNOLOGY VOLUME 34 NUMBER 2 FEBRUARY 2016
and Supplementary Tables 11 and 12; refs. 9,10). The chemical shift of each nucleus is an absolute frequency position, and perturbations in the higher-order structure, such as altered hydrogen bonding, can influence the local electronic environments of nuclei, leading to changes in chemical shifts. Thus, amide 1HN and 15N chemical shift changes can be assessed individually using RMSD from the average values or in aggregate by CCSD (which involves taking a weighted average of the observed changes in 1HN and 15N shift values9). With either of these methods, the chemical shift assignment of the primary sequence allows atomic-level mapping of spectral signals to a known protein structure, but this is not required for the method to be useful. From RMSD and CCSD analyses, an experimental precision of 8 p.p.b. was determined across the six spectrometers in the four laboratories. Notably, 8 p.p.b. is close to the digital resolution of approximately 5 p.p.b. of an individual spectrum (see Supplementary Methods), which establishes a threshold for the precision of the measurement. Similarly, an intralaboratory precision of approximately 4 p.p.b. was found that falls well within the digital resolution of a spectrum (Supplementary Table 12), and a related study found an experimental precision for the same sample of 2.4 p.p.b.10. These precision limits are well below any chemical shift changes that could be induced by a significant structural change (such as a point mutation or a modification of a residue by oxidation or local conformational change). These approaches also readily identify the temperature deviation of the non-calibrated spectrometers (Fig. 1b), further demonstrating the need for matched experimental conditions if the method is to be used as a structure comparability tool. As expected, the recalibrated spectra were well within the determined experimental precision (Fig. 1c). Although comparison of spectral overlays and chemical shifts provides the most straightforward method for the analysis of two or three samples, it can be cumbersome when large numbers of datasets need to be compared, as in the monitoring of lot-to-lot consistency; in such instances a multivariate statistical analysis approach may be more appropriate. Here, we used PCA because it provides a single readout of variance in all 139
higher-order structure. The results clearly demonstrate both the precision and the robustness of 2D-NMR as a multifrequencybased higher-order structure assessment tool. The data acquired during this study show minimal measurement drift attributable to the nine-month period of the
study and across the various instruments and laboratories. As traceable reference values are established using this technique, a comparability exercise on the higherorder structure of a recombinant protein therapeutic could be performed using the NMR signature of a comparator from a
a
105 Gln134 Ala6
125
110
Leu71 126 8.5
115
120
N (p.p.m.)
8.8 8.7 8.6
15
Gln70
109.2 109.4
125
109.6 5.95
10
9
8 1 H (p.p.m.)
7
b
c
0.040
0.040
0.030
0.030
CCSD (p.p.m.)
CCSD (p.p.m.)
2D-NMR spectra collected for filgrastim. The PCA plot shown in Figure 1d was calculated with all peaks in the 2D-NMR spectrum with a defined intensity threshold (see Supplementary Methods). This analysis included peak shifts due to sample temperature differences, the presence of impurities (for example, oxidized species in the system suitability sample) and variation in signal intensities resulting from spectrometerdependent line widths. For each spectrometer except the MPA 600, all drug products are tightly clustered because of the high similarity of the higher-order structure. The slightly wider spread of the MPA 600 data is attributed to a difference in the performance of the pulsed NMR method chosen to obtain the 2D map on this spectrometer as well as to aging of the samples over time (Supplementary Table 8). NIST 900 data re-collected after one year on the same samples confirmed this interpretation (Supplementary Fig. 7). Similar to the chemical shift–based analysis, the PCA test clearly distinguishes the two samples with temperature deviation, whereas the 15N-GCSF system suitability sample is found to cluster in its own region mainly because of the differences in protein impurities. To our knowledge, this is the first reported interlaboratory study of a high-resolution 2D-NMR method to assess biotherapeutic
5.90
130 6
Figure 1 Spectral and statistical comparisons of 0.020 0.020 NMR data. (a) Overlay plot of the same region on the same sample from Amgen at four fields and 0.010 0.010 six instruments: NIST 900 (purple), NIST 600 (cyan), HC 700 (black), HC 600 (red), FDA 500 (green) and MPA 600 MHz (blue). Note that all 0 0 0 40 80 120 160 0 40 80 120 160 resonances except data from HC 700 and HC 600 are perfectly overlaid under the blue peaks. This Sequence Sequence is highlighted in the upper left side inset showing an expansion of the regions containing signals HC700 MPA600 from the amides of Gln134, Gln70, Leu71 and 2 Ala6. In the lower right inset, a weaker peak is FDA plotted using different contours to show that it 500 1 NIST600 is observed in all spectra. Additional peaks in the lower right corner of the spectra arise from 0 HC600 unsuppressed residual signal from water in HC700 some spectra. (b) An example of the combined –1 HC600 NIST900 chemical shift difference (CCSD) plots for the –2 system suitability sample, 15N-met-G-CSF, as a function of sequence (NIST 900 (plus), NIST –3 600 (star), HC 700 (circle), HC 600 (square), FDA 500 (diamond) and MPA 600 (triangle)) –4 with the sample temperature difference on the 5 HC instruments. (c) Same as b after temperature 0 15 Sco –2 N-G-CSF res 0 on P –5 calibration. The reference chemical shift was 2 0%) C1 .6 7 –10 (1 4 (53. C2 based on average shift from NIST, FDA and 25% s on P Score ) MPA. The horizontal bar indicates the measured experimental precision limit of 8 p.p.b. (d) A plot of the result of the principal-component analysis performed on data of the four drug products recorded at the four laboratories on six instruments, FDA 500 (dark blue); NIST 900 (blue, the cluster at ORIGIN); NIST 600 (turquoise); HC 700 (green); HC 600 (yellow); and MPA 600 (orange). Dashed ellipses show the relative clustering of data from each laboratory. For this panel, the temperatures during collection of HC 600 and HC 700 data were not calibrated.
d
Scores on PC 3 (7.48%)
npg
© 2016 Nature America, Inc. All rights reserved.
CORRESPONDENCE
140
VOLUME 34 NUMBER 2 FEBRUARY 2016 NATURE BIOTECHNOLOGY
CORRESPONDENCE validated database without the need to record its spectra again. Utilization of NMR spectral analyses by both sponsors of biosimilars and originators will provide greater assurance of drug product quality to the regulatory agencies.
npg
© 2016 Nature America, Inc. All rights reserved.
DISCLAIMERS The findings and conclusions in this article have not been formally disseminated by the Food and Drug Administration and should not be construed to represent any Agency determination or policy. Certain commercial equipment, instruments and materials are identified in this paper in order to specify the experimental procedure. Such identification does not imply recommendation or endorsement by the National Institute of Standards and Technology, nor does it imply that the material or equipment identified is necessarily the best available for the purpose. Note: Any Supplementary Information and Source Data files are available in the online version of the paper (doi:10.1038/nbt.3474). COMPETING FINANCIAL INTERESTS The authors declare no competing financial interests.
Houman Ghasriani1, Derek J Hodgson2, Robert G Brinson3, Ian McEwen4, Lucinda F Buhse1, Steven Kozlowski5, John P Marino3, Yves Aubin2 & David A Keire1 1US Food and Drug Administration, Center
for Drug Evaluation and Research, Division of Pharmaceutical Analysis, St. Louis, Missouri, USA. 2Centre for Biologics Evaluation, Biologics and Genetic Therapies Directorate, Health
Canada, Ottawa, Ontario, Canada. 3Institute for Bioscience and Biotechnology Research, National Institute of Standards and Technology, Rockville, Maryland, USA. 4Medical Products Agency of Sweden, Uppsala, Sweden. 5US Food and Drug Administration, Center for Drug Evaluation and Research, Office of Biotechnology Products, Silver Spring, Maryland, USA. e-mail: [email protected], [email protected] or [email protected] 1. Health Canada. Guidance for sponsors: information and submission requirements for subsequent entry biologics (SEBs) (publication 2010/03/05) (Health Canada Publications, 2010). 2. EMEA. Comparability of biotechnological/biological products subject to changes in their manufacturing process (CPMP/ICH/5721/03) (European Medicines Agency, 2006). 3. US Food and Drug Administration. Guidance for industry: quality considerations in demonstrating biosimilarity to a reference protein product (UCM291134) (US FDA Office of Communications, 2012). 4. US FDA. Guidance for industry: scientific considerations in demonstrating biosimilarity to a reference product (UCM291128) (US FDA Office of Communications, 2012). 5. Gabrielson, J.P. & Weiss, W.F. 4th. J. Pharm. Sci. 104, 1240–1245 (2015). 6. Aubin, Y., Gingras, G. & Sauvé, S. Anal. Chem. 80, 2623–2627 (2008). 7. Aubin, Y., Hodgson, D.J., Thach, W.B., Gingras, G. & Sauvé, S. Pharm. Res. 32, 3365–3375 (2015). 8. Baxter, N.J. & Williamson, M.P. Temperature dependence of 1H chemical shifts in proteins. J. Biomol. NMR 9, 359–369 (1997). 9. Williamson, M.P. Prog. Nucl. Magn. Reson. Spectrosc. 73, 1–16 (2013). 10. Arbogast, L.W., Brinson, R.G. & Marino, J.P. Anal. Chem. 87, 3556–3561 (2015).
Evolving Japanese regulations on companion diagnostics To the Editor: Precision medicine involves the identification of a group of patients on the basis of a biomarker measured via a companion diagnostic who are then treated with a therapeutic targeted against that biomarker. The Japanese regulatory agency responsible for overseeing the regulatory oversight of companion diagnostics is the Pharmaceuticals and Medical Devices Agency (PMDA; Tokyo), which works with the Ministry of Health, Labor and Welfare (MHLW; Tokyo). In September 2014, the PMDA held a workshop on companion diagnostics that brought together >400 participants from academia, industry and regulatory agencies. The workshop identified the evaluation of concordance among different diagnostics targeting the same marker and the assessment of multiplex diagnostics as two key outstanding challenges. In the following correspondence, we briefly introduce PMDA’s and MHLW’s activities with
regard to companion diagnostics, compare key differences among Japanese, US and European Union (EU; Brussels) regulations, and conclude by describing challenges relating to companion diagnostics discussed at the workshop. The MHLW categorizes in vitro diagnostics (IVDs) into class I products (self-certified), class II products (subject to third-party certification) and class III products (subject to PMDA review under marketing authorization applications (MAAs) and approved by the MHLW), mainly depending on risk profile. Class I or II products without existing standards, like class III products, are also subject to PMDA review. Companion diagnostics generally fall under class III and usually require review not only by PMDA officers (standard MAAs) but also by outside advisory experts. In July 2013, the PMDA published its “Notification on approval applications for in vitro
NATURE BIOTECHNOLOGY VOLUME 34 NUMBER 2 FEBRUARY 2016
companion diagnostics and corresponding therapeutic products” document1,2, which defines companion diagnostics as IVDs for use in tandem with a specific drug. Table 1 compares and contrasts PMDA regulatory assessment of companion diagnostics with oversight by US Food and Drug Administration (FDA; Rockville, MD) and by the European Union. The FDA finalized guidance3,4 departs from the Japanese notification1 in two key respects. First, the FDA’s guidance notes that companion diagnostics and corresponding drugs should be approved at the same time, whereas the Japanese notification specifies that MAAs of therapeutic products and corresponding companion diagnostics should be submitted at the same time. By emphasizing concurrent submission, the Japanese regulation encourages sponsors planning to develop companion diagnostics and their corresponding drugs to cooperate with each other from the early stages of product development stage; such an approach allows a companion diagnostic to be approved earlier than its corresponding therapeutic, thereby enabling testing laboratories to be prepared for its use in anticipation of drug approval. Second, the FDA’s guidance4 mentions situations in which a therapeutic product to treat serious or life-threatening conditions can be approved without a companion diagnostic. In contrast, the Q&A in the Japanese notification2 specifies only that the acceptability of a submission that is delayed for an unavoidable reason will be judged on a case-by-case basis. A later MHLW/PMDA guidance published in December 2013—the “Technical guidance on development of in vitro companion diagnostics and corresponding therapeutic products”5— differs from FDA oversight in another two major respects: policy on biomarker-negative patients in clinical trials and retrospective analyses of biomarkers. The issue of biomarker-negative patients relates to individuals who on the basis of a companion diagnostic test lack a biomarker but nevertheless still clinically respond to therapies thought to target the same biomarker. Biomarker-negative responders may be attributable to several factors, including low sensitivity of diagnostics (especially immunohistochemistry (IHC) tests), off-target effects of molecularly targeted drugs, poor quality of biospecimens, and (in oncology) intratumor heterogeneity. A case in point is anti–epidermal growth factor receptor 141
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© 2016 Nature America, Inc. All rights reserved.
Precision and robustness of 2D-NMR for structure assessment of filgrastim biosimilars To the Editor: With the advent of biosimilar versions of brand biologics, regulatory authorities in all major jurisdictions throughout the world have developed guidance documents to facilitate their approval1–4. The common theme in the new documents is the stipulation that sponsors must demonstrate biosimilarity between their proposed product and an approved reference product using state-of-the-art analytical technologies. In the US guidance documents, a “totality of evidence” approach is described that can be used to establish the degree of similarity and guide regulatory decision-making3,4. Higher-order structure is an important quality attribute of biosimilars that must be assessed by comparison to the reference licensed drug. To date, higher-order structure has been evaluated with low-resolution techniques, such as circular dichroism, Fourier transform infrared and Raman spectroscopies, and indirectly with several biological and stability assays5. In 2008, a two-dimensional nuclear magnetic resonance (2D-NMR) spectroscopy approach was first applied to the high-resolution assessment of the higher-order structure of a native recombinant protein therapeutic6. The technique resolves, in a 2D frequency map, the positions of proton–nitrogen atom pairs from each amide and amino group in a biologic molecule. Each signal correlates to the specific local chemical and structural environment of the atom pair; thus, the entire spectrum provides a comprehensive readout of the drug substance conformation along the polypeptide chain at atomic resolution, providing a potentially useful tool to establish drug substance consistency across manufacturing changes or comparability of the higher-order structure of biosimilars. In this work, an interlaboratory comparative study was performed on filgrastim (methionyl granulocyte colony-stimulating factor; Met-G-CSF) to demonstrate the precision and robustness of the 2D-NMR approach. Filgrastim was selected because of its therapeutic importance, because the drug had been characterized by NMR7 and because a number of filgrastim biosimilars have already been approved in Europe, the United States and other jurisdictions. Here, a USapproved originator product (Neupogen) and three unapproved, non-US-sourced
filgrastim products were used in their fully formulated states (Supplementary Table 1) to prepare a set of four samples for analysis using heteronuclear 2D-NMR correlation at 15N natural isotopic abundance. Spectra were acquired on the same samples on six different spectrometers, at four different field strengths ranging from 500 MHz to 900 MHz, in four different laboratories (for instrument specifications and experimental parameters, see Supplementary Tables 2–9). All the NMR data were analyzed and evaluated using the same software packages for visual evaluation, chemical shift analysis and principal-component analysis (PCA) to assess spectral similarity through multiple approaches. The interlaboratory study data show that the resolution of the NMR method allows one to quickly visualize the high degree of similarity of the spectral patterns obtained from the 2D-NMR experiments run on different spectrometers. In this respect, visual comparison of spectral overlays allows an operator to directly assess sample similarity (Fig. 1a, Supplementary Table 10 and Supplementary Figs. 1–4). Differences between two spectral patterns can result from variation in solution conditions (such as pH or ionic strength), variation in the temperature of the sample, and/or differences in the higher-order structure of the protein. As an example, in our study, the overlay of spectra acquired for the same filgrastim sample on two spectrometers revealed a number of peak signal deviations that could be mapped to solvent-exposed residues (Fig. 1a, inset). Four representative residues in loop regions that exhibited these deviations are shown in Supplementary Figure 2b. We found that these differences could be explained by differences in temperature of 2 °C and 4 °C for the HC 700 and HC 600 spectrometers, respectively. The change of temperature does not affect all amide resonances equally7 and has been described by Baxter and Williamson8. Proper instrument calibration removed these discrepancies (Supplementary Fig. 2c). For a more quantitative analysis, chemical shifts of each individual signal in the 2D map were compared using a root mean square deviation (RMSD) analysis or combined chemical shift difference (CCSD) methods (Fig. 1b,c, Supplementary Figs. 5 and 6,
NATURE BIOTECHNOLOGY VOLUME 34 NUMBER 2 FEBRUARY 2016
and Supplementary Tables 11 and 12; refs. 9,10). The chemical shift of each nucleus is an absolute frequency position, and perturbations in the higher-order structure, such as altered hydrogen bonding, can influence the local electronic environments of nuclei, leading to changes in chemical shifts. Thus, amide 1HN and 15N chemical shift changes can be assessed individually using RMSD from the average values or in aggregate by CCSD (which involves taking a weighted average of the observed changes in 1HN and 15N shift values9). With either of these methods, the chemical shift assignment of the primary sequence allows atomic-level mapping of spectral signals to a known protein structure, but this is not required for the method to be useful. From RMSD and CCSD analyses, an experimental precision of 8 p.p.b. was determined across the six spectrometers in the four laboratories. Notably, 8 p.p.b. is close to the digital resolution of approximately 5 p.p.b. of an individual spectrum (see Supplementary Methods), which establishes a threshold for the precision of the measurement. Similarly, an intralaboratory precision of approximately 4 p.p.b. was found that falls well within the digital resolution of a spectrum (Supplementary Table 12), and a related study found an experimental precision for the same sample of 2.4 p.p.b.10. These precision limits are well below any chemical shift changes that could be induced by a significant structural change (such as a point mutation or a modification of a residue by oxidation or local conformational change). These approaches also readily identify the temperature deviation of the non-calibrated spectrometers (Fig. 1b), further demonstrating the need for matched experimental conditions if the method is to be used as a structure comparability tool. As expected, the recalibrated spectra were well within the determined experimental precision (Fig. 1c). Although comparison of spectral overlays and chemical shifts provides the most straightforward method for the analysis of two or three samples, it can be cumbersome when large numbers of datasets need to be compared, as in the monitoring of lot-to-lot consistency; in such instances a multivariate statistical analysis approach may be more appropriate. Here, we used PCA because it provides a single readout of variance in all 139
higher-order structure. The results clearly demonstrate both the precision and the robustness of 2D-NMR as a multifrequencybased higher-order structure assessment tool. The data acquired during this study show minimal measurement drift attributable to the nine-month period of the
study and across the various instruments and laboratories. As traceable reference values are established using this technique, a comparability exercise on the higherorder structure of a recombinant protein therapeutic could be performed using the NMR signature of a comparator from a
a
105 Gln134 Ala6
125
110
Leu71 126 8.5
115
120
N (p.p.m.)
8.8 8.7 8.6
15
Gln70
109.2 109.4
125
109.6 5.95
10
9
8 1 H (p.p.m.)
7
b
c
0.040
0.040
0.030
0.030
CCSD (p.p.m.)
CCSD (p.p.m.)
2D-NMR spectra collected for filgrastim. The PCA plot shown in Figure 1d was calculated with all peaks in the 2D-NMR spectrum with a defined intensity threshold (see Supplementary Methods). This analysis included peak shifts due to sample temperature differences, the presence of impurities (for example, oxidized species in the system suitability sample) and variation in signal intensities resulting from spectrometerdependent line widths. For each spectrometer except the MPA 600, all drug products are tightly clustered because of the high similarity of the higher-order structure. The slightly wider spread of the MPA 600 data is attributed to a difference in the performance of the pulsed NMR method chosen to obtain the 2D map on this spectrometer as well as to aging of the samples over time (Supplementary Table 8). NIST 900 data re-collected after one year on the same samples confirmed this interpretation (Supplementary Fig. 7). Similar to the chemical shift–based analysis, the PCA test clearly distinguishes the two samples with temperature deviation, whereas the 15N-GCSF system suitability sample is found to cluster in its own region mainly because of the differences in protein impurities. To our knowledge, this is the first reported interlaboratory study of a high-resolution 2D-NMR method to assess biotherapeutic
5.90
130 6
Figure 1 Spectral and statistical comparisons of 0.020 0.020 NMR data. (a) Overlay plot of the same region on the same sample from Amgen at four fields and 0.010 0.010 six instruments: NIST 900 (purple), NIST 600 (cyan), HC 700 (black), HC 600 (red), FDA 500 (green) and MPA 600 MHz (blue). Note that all 0 0 0 40 80 120 160 0 40 80 120 160 resonances except data from HC 700 and HC 600 are perfectly overlaid under the blue peaks. This Sequence Sequence is highlighted in the upper left side inset showing an expansion of the regions containing signals HC700 MPA600 from the amides of Gln134, Gln70, Leu71 and 2 Ala6. In the lower right inset, a weaker peak is FDA plotted using different contours to show that it 500 1 NIST600 is observed in all spectra. Additional peaks in the lower right corner of the spectra arise from 0 HC600 unsuppressed residual signal from water in HC700 some spectra. (b) An example of the combined –1 HC600 NIST900 chemical shift difference (CCSD) plots for the –2 system suitability sample, 15N-met-G-CSF, as a function of sequence (NIST 900 (plus), NIST –3 600 (star), HC 700 (circle), HC 600 (square), FDA 500 (diamond) and MPA 600 (triangle)) –4 with the sample temperature difference on the 5 HC instruments. (c) Same as b after temperature 0 15 Sco –2 N-G-CSF res 0 on P –5 calibration. The reference chemical shift was 2 0%) C1 .6 7 –10 (1 4 (53. C2 based on average shift from NIST, FDA and 25% s on P Score ) MPA. The horizontal bar indicates the measured experimental precision limit of 8 p.p.b. (d) A plot of the result of the principal-component analysis performed on data of the four drug products recorded at the four laboratories on six instruments, FDA 500 (dark blue); NIST 900 (blue, the cluster at ORIGIN); NIST 600 (turquoise); HC 700 (green); HC 600 (yellow); and MPA 600 (orange). Dashed ellipses show the relative clustering of data from each laboratory. For this panel, the temperatures during collection of HC 600 and HC 700 data were not calibrated.
d
Scores on PC 3 (7.48%)
npg
© 2016 Nature America, Inc. All rights reserved.
CORRESPONDENCE
140
VOLUME 34 NUMBER 2 FEBRUARY 2016 NATURE BIOTECHNOLOGY
CORRESPONDENCE validated database without the need to record its spectra again. Utilization of NMR spectral analyses by both sponsors of biosimilars and originators will provide greater assurance of drug product quality to the regulatory agencies.
npg
© 2016 Nature America, Inc. All rights reserved.
DISCLAIMERS The findings and conclusions in this article have not been formally disseminated by the Food and Drug Administration and should not be construed to represent any Agency determination or policy. Certain commercial equipment, instruments and materials are identified in this paper in order to specify the experimental procedure. Such identification does not imply recommendation or endorsement by the National Institute of Standards and Technology, nor does it imply that the material or equipment identified is necessarily the best available for the purpose. Note: Any Supplementary Information and Source Data files are available in the online version of the paper (doi:10.1038/nbt.3474). COMPETING FINANCIAL INTERESTS The authors declare no competing financial interests.
Houman Ghasriani1, Derek J Hodgson2, Robert G Brinson3, Ian McEwen4, Lucinda F Buhse1, Steven Kozlowski5, John P Marino3, Yves Aubin2 & David A Keire1 1US Food and Drug Administration, Center
for Drug Evaluation and Research, Division of Pharmaceutical Analysis, St. Louis, Missouri, USA. 2Centre for Biologics Evaluation, Biologics and Genetic Therapies Directorate, Health
Canada, Ottawa, Ontario, Canada. 3Institute for Bioscience and Biotechnology Research, National Institute of Standards and Technology, Rockville, Maryland, USA. 4Medical Products Agency of Sweden, Uppsala, Sweden. 5US Food and Drug Administration, Center for Drug Evaluation and Research, Office of Biotechnology Products, Silver Spring, Maryland, USA. e-mail: [email protected], [email protected] or [email protected] 1. Health Canada. Guidance for sponsors: information and submission requirements for subsequent entry biologics (SEBs) (publication 2010/03/05) (Health Canada Publications, 2010). 2. EMEA. Comparability of biotechnological/biological products subject to changes in their manufacturing process (CPMP/ICH/5721/03) (European Medicines Agency, 2006). 3. US Food and Drug Administration. Guidance for industry: quality considerations in demonstrating biosimilarity to a reference protein product (UCM291134) (US FDA Office of Communications, 2012). 4. US FDA. Guidance for industry: scientific considerations in demonstrating biosimilarity to a reference product (UCM291128) (US FDA Office of Communications, 2012). 5. Gabrielson, J.P. & Weiss, W.F. 4th. J. Pharm. Sci. 104, 1240–1245 (2015). 6. Aubin, Y., Gingras, G. & Sauvé, S. Anal. Chem. 80, 2623–2627 (2008). 7. Aubin, Y., Hodgson, D.J., Thach, W.B., Gingras, G. & Sauvé, S. Pharm. Res. 32, 3365–3375 (2015). 8. Baxter, N.J. & Williamson, M.P. Temperature dependence of 1H chemical shifts in proteins. J. Biomol. NMR 9, 359–369 (1997). 9. Williamson, M.P. Prog. Nucl. Magn. Reson. Spectrosc. 73, 1–16 (2013). 10. Arbogast, L.W., Brinson, R.G. & Marino, J.P. Anal. Chem. 87, 3556–3561 (2015).
Evolving Japanese regulations on companion diagnostics To the Editor: Precision medicine involves the identification of a group of patients on the basis of a biomarker measured via a companion diagnostic who are then treated with a therapeutic targeted against that biomarker. The Japanese regulatory agency responsible for overseeing the regulatory oversight of companion diagnostics is the Pharmaceuticals and Medical Devices Agency (PMDA; Tokyo), which works with the Ministry of Health, Labor and Welfare (MHLW; Tokyo). In September 2014, the PMDA held a workshop on companion diagnostics that brought together >400 participants from academia, industry and regulatory agencies. The workshop identified the evaluation of concordance among different diagnostics targeting the same marker and the assessment of multiplex diagnostics as two key outstanding challenges. In the following correspondence, we briefly introduce PMDA’s and MHLW’s activities with
regard to companion diagnostics, compare key differences among Japanese, US and European Union (EU; Brussels) regulations, and conclude by describing challenges relating to companion diagnostics discussed at the workshop. The MHLW categorizes in vitro diagnostics (IVDs) into class I products (self-certified), class II products (subject to third-party certification) and class III products (subject to PMDA review under marketing authorization applications (MAAs) and approved by the MHLW), mainly depending on risk profile. Class I or II products without existing standards, like class III products, are also subject to PMDA review. Companion diagnostics generally fall under class III and usually require review not only by PMDA officers (standard MAAs) but also by outside advisory experts. In July 2013, the PMDA published its “Notification on approval applications for in vitro
NATURE BIOTECHNOLOGY VOLUME 34 NUMBER 2 FEBRUARY 2016
companion diagnostics and corresponding therapeutic products” document1,2, which defines companion diagnostics as IVDs for use in tandem with a specific drug. Table 1 compares and contrasts PMDA regulatory assessment of companion diagnostics with oversight by US Food and Drug Administration (FDA; Rockville, MD) and by the European Union. The FDA finalized guidance3,4 departs from the Japanese notification1 in two key respects. First, the FDA’s guidance notes that companion diagnostics and corresponding drugs should be approved at the same time, whereas the Japanese notification specifies that MAAs of therapeutic products and corresponding companion diagnostics should be submitted at the same time. By emphasizing concurrent submission, the Japanese regulation encourages sponsors planning to develop companion diagnostics and their corresponding drugs to cooperate with each other from the early stages of product development stage; such an approach allows a companion diagnostic to be approved earlier than its corresponding therapeutic, thereby enabling testing laboratories to be prepared for its use in anticipation of drug approval. Second, the FDA’s guidance4 mentions situations in which a therapeutic product to treat serious or life-threatening conditions can be approved without a companion diagnostic. In contrast, the Q&A in the Japanese notification2 specifies only that the acceptability of a submission that is delayed for an unavoidable reason will be judged on a case-by-case basis. A later MHLW/PMDA guidance published in December 2013—the “Technical guidance on development of in vitro companion diagnostics and corresponding therapeutic products”5— differs from FDA oversight in another two major respects: policy on biomarker-negative patients in clinical trials and retrospective analyses of biomarkers. The issue of biomarker-negative patients relates to individuals who on the basis of a companion diagnostic test lack a biomarker but nevertheless still clinically respond to therapies thought to target the same biomarker. Biomarker-negative responders may be attributable to several factors, including low sensitivity of diagnostics (especially immunohistochemistry (IHC) tests), off-target effects of molecularly targeted drugs, poor quality of biospecimens, and (in oncology) intratumor heterogeneity. A case in point is anti–epidermal growth factor receptor 141
