QbD Track 2: Real Time Release Testing/New Technologies IFPAC-2016

QbD/PAT/RTRT application and regulatory interaction in Japan

Hiroshi Nakagawa, Ph.D Formulation Technology Research Laboratories, Daiichi Sankyo Co., Ltd. January 26, 2016

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RTRT approval in April 2011 (DVT: Deep vein thrombosis)

Appearance, ID, UDU, Dissolution and Assay

Edoxaban Tablets (Lixiana®: Japan)

15-mg tablets 30-mg tablets

RTRT approval in September 2014 (AF: Atrial Fibrillation/VTE: Venous thromboembolism)

Dose addition and Dissolution design space change

60-mg tablets

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CQA

MA MA MA MA MA MA MA p-CMA

PP PP PP PP PP PP PP PP PP

p-CPP

p-CPP

p-CPP

p-CPP

MA MA MA MA

MA MA

p-CMA

p-CMA

p-CMA

CMA

CMA

CPP

PP

PP

Fish bone, PHA, FMEA

FMEA

Fish bone, PHA, FMEA

FMEA

PAT

CPP

Attribute based design space

RTRT

CMA (Critical Material Attribute) Based Approach

Enhanced QbD Approach in Edoxaban Tablets

Advantage of CMA Based Approach

Design space

Tableting Pressure Rotational Speed Feed Rate Turn Table Rotational Speed

API particle size Tablet Hardness

Dissolution Equipment A Equipment B

PAT PAT

CPP CPP Milling Tableting

Ex. In case that two CMAs of API particle size and tablet hardness affect CQA of dissolution (General example)

CMA

Pros Cons Design space portability for manufacturing site/equipment change Scale independent

Finding CMA with comprehensive risk assessment

CMA monitoring method development

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Control Strategy in Edoxaban Tablets Manufacturing

Film-Coating

Drug Product

Drug Substance

Packaging

Blending

Tableting

Granulation

Assay Uniformity of Dosage Units (UDU) Dissolution

RTRT has been applied to all spec. items for Edoxaban Tablets in Japan market.

RTRT is applied when CMAs are controlled within design spaces.

RTRT is applied when the test items are assured in the manufacturing area.

Appearance Identification

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Risk Assessment for Assay and UDU

Risk Assessment of CMAs affecting CQAs of Assay and UDU

Reference: 2.3 Quality Overall Summary; Sakura Tablet (2008)

CQA UDU/Assay p-CMA

Blend uniformity

Blending

Tableting

p-CMA API content in granules

p-CMA Tablet weight

p-CMA Tablet weight Variation

p-CMA Granule segregation

CQA of UDU = f (CMA of blend uniformity, API content in granules, tablet weight/variation)

Low risk

No need of individual tablet assay approach (e.g. Large N)

CQA of Assay = f (CMA of API content, tablet weight)

First principle model

NIR

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Control strategy for CQA of assay

X: Assay Xa: API content in granules for tableting (% of the theoretical concentration) Wa: Uncoated tablet weight (% of the theoretical weight)

𝑿 =𝑿𝑿 · 𝑾𝑿𝟏𝟏𝟏

Design space inside the two walls the assay

meets the specification

*Theoretical uncoated tablet weight for each strength is established as 100%.

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Control strategy for CQA of UDU (1/2)

AV: Acceptance value of UDU Xa: API content in granules for tableting (% of the theoretical concentration)

Wa: Uncoated tablet weight (% of the theoretical weight)

sx: Blend uniformity (RSD, %)

sw: Uncoated tablet weight variation (RSD, %)

AV (%) = │M- X│+ ks <JP/USP/Ph.Eur.>

X < 98.5% 98.5% ≤ X ≤ 101.5 % X> 101.5 %

M 98.5% X 101.5 %

N. Katori; N. Aoyagi; S. Kojima; Chem. Pharm. Bull., 49 (11) 2001, 1412- 1419

= │M− 𝑿𝑿 · 𝑾𝑿100

│ + 𝑘 sw2( 𝑿𝑿100

)2 + sx2( 𝑾𝑿100

)2

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Uncoated tablet weight* API content in granules

for tableting

Uncoated

tablet weight

variation

0%

3%

4%

5%

6%

95% 96%

98% 97%

99%

101% 100%

105%

102% 103%

104%

90% 95%

100% 105%

110%

* Theoretical uncoated tablet weight for each dose is established as 100%.

1%

2%

Design space inside the tunnel the UDU

meets the specification (AV ≤15.0)

Design space plotted at sx = 5.0% (RSD) blend uniformity → Applied worst case value of blend uniformity to realize the tight quality control T. Garcia et al., J. Pharm. Innov., (10) 2015, 76 - 83

Control strategy for CQA of UDU (2/2)

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Integrated Design Space for Assay and UDU

Integrated Design Space*1 Overlay of design spaces

for Assay and UDU (Inside of the tunnel meets the

specification for Assay and UDU)

*1: Design space plotted at sx=5.0% (RSD) blend uniformity *2: Theoretical uncoated tablet weight for each strength is established as 100%.

Assay and UDU can be assured when the combination of CMAs is within the tunnel.

Validation of Design Space for Assay and UDU (1/2)

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Comparison between conventional and RTRT methods

0%

1%

2%

3%

4%

5%

6%

95% 96%

98% 97%

99%

101% 100%

105%

102% 103%

104%

90% 95%

100% 105%

110%

1

12

13

9 8

7

2 3

10

11 5

6 4

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Validation of Design Space for Assay and UDU (2/2)

Fig. Validation Results for UDU Fig. Validation Results for Assay

Values calculated by conventional and RTRT methods were well correlated in both Assay and UDU (BU: actual).

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Pros of 1st Principle Assay and UDU Control Strategy

One NIR model predicting API content is commonly used for all strengths to calculate Assay and UDU.

IPC/Spec. API content in granules

Spec. Tablet assay

Change of target tablet weight depending on the API content in granules

No need of dose dependent NIR model

Quality Control with Design Space Flexibility Ex. Assay

Assay can be controlled close to the target value by changing the uncoated tablet weight within design space.

Key

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API Content in Granules Prediction by NIR

・・

99.8%

100.5%

70.2%

115.7%

80.0%

108.1%

97.9%

X Y

Calibration set

Unknown sample

100.0%

Developed calibration model

2. Parameter Selection Pretreatment, Wavenumber, Spectral analysis (e.g. PLS), Number of latent variables

Routine measurement NIR spectra API content

3. Model Evaluation Correlate coefficient, RMSECV, Loading, Regression coefficient, Score, etc.

4. Analytical Validation

Specificity, Linearity, Range Accuracy, Precision, Robustness

1. Data Acquisition

H. Nakagawa; M. Kano; S. Hasebe; T. Miyano; T. Watanabe; N. Wakiyama; Int. J. Pharm., 471 (2014) 264-275

NIR model development

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Establishment of Calibration Set

＋

Concept of Calibration Set (NIR spectra)

Samples with purposeful variations of API content (e.g. 70% to 130%)

Samples with variations affecting NIR spectra (e.g. variations of particle size)

＋

Samples manufactured with commercial equipment (e.g. Scale up study samples)

Key for robust model development Selection of samples affecting NIR spectra in routine manufacturing

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Model Evaluation / Analytical Validation

Measurement Value by HPLC [%]

Pred

ictio

n Va

lue

by N

IR [%

]

Specificity Linearity Accuracy Precision Range Robustness

API peak Correlation coefficient

SEP RSD of repeated measurements

Validated range

Variations of environment

Reference • Guidance for Industry, Development and Submission of Near Infrared Analytical Procedures (2015, FDA) • Guideline on the use of near infrared spectroscopy by the pharmaceutical industry and the data requirements for new submissions and variations (2014, EMA) • Standard Practices for Infrared Multivariate Quantitative Analysis (E1655, ASTM), etc.

Dialogue with PMDA (1/3)

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CQA

Critical Quality Attributes (ex. assay, CU, dissolution)

CPP Critical Process Parameters that

ensure CMAs

CPP Critical Process Parameters that

ensure CQA

CMA based Approach CPP based approach

CMA

Critical Material Attributes that assure CQA

CQA

Critical Quality Attributes (ex. assay, CU, dissolution)

Regulatory Flexibility in CMA Based Approach

Design Space

Potential to have an adverse effect on CQ

A

High

Low

Regulatory flexibility for

change control

CMA based approach was applied to new QbD mock sponsored by MHLW: Sakura bloom Tablets (2015)

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Event check

SST, etc Trend analysis

Change control, QA judgment

Appropriateness of prediction models

Quality Assurance in RTRT

CQA Std

Max

Min

Trend change

Comparison with conventional testing

Periodical check Daily check

Actual Predict Prediction error

Model check (and updated)

Countermeasures for unexpected variations in model development stage

Model maintenance trigger

Model Maintenance

Dialogue with PMDA (2/3)

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Development of NIR model

Validation of NIR model

Transfer of NIR model (Laboratory to Plant)

Routine measurement

Laboratory - Development

Plant - Operation

Model update and

Re-validation

Model Maintenance

Trigger of model maintenance

In case that model update according to SOP is difficult

Close cooperation between laboratory and plant

Verification of prediction error

(Comparison with conventional method)

Acceptable error

Unacceptable error

Dialogue with PMDA (3/3) Quality Management System for NIR Model

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Queries from PMDA

Queries from PMDA 1st submission

(April 2011) 2nd submission

(September 2014) Total

General 4 4 8

QbD/PAT/RTRT related 85 8 93

Total 89 12 101

All the queries had been successfully solved by close-dialogue with PMDA.

Significant decrease of queries in 2nd submission based on the close-dialogue with PMDA in 1st submission

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Conclusion

Edoxaban tablets 15 mg, 30 mg, and 60 mg were approved as RTRT products in Japan. CMA based enhanced QbD approach, in which a design space is constructed only using CMAs, was applied to Edoxaban tablets. e.g., Assay and UDU design space was constructed using four CMAs of 1st principle equation based on compendial requirements. A lot of queries were inquired by PMDA, but all had been successfully solved by close-dialogue.

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Acknowledgment

Formulation Tomoyuki Watanabe Naoki Wakiyama Tatsuya Suzuki Masazumi Kojima Hidehiro Imai Koichi Ishidoh Kazuko Maeda Makoto Kamada Jin Hisazumi Jin Maeda Masatomo Ito Hideaki Tanabe Takuya Miyano Kazuhiro Matsuura Yoshito Kikkawa Shuichi Tanabe Takafumi Kato Rie Saguchi

CMC Takeshi Hamaura Shuichi Ando Motonori Kidokoro Hiromi Morita Kenichi Enokita Hiroyuki Nakata Kyoko Nakanishi

Analytical Motomu Ohara Tadanobu Takatani Hiroki Hifumi

Plant Jun Hishida Katsuhiko Nagao Tsuyoshi Tanaka Satoshi Osaki Hiroaki Inoue Eiji Kawai Shigenari Sugaya Takahiko Nuga Yasuhiro Maniwa Tomohiro Yoshida Ryota Suzuki Masaaki Koyama Masanobu Kabasawa Other Company

Hiroaki Nakagami Takashi Maehara

Headquarters Chiaki Matsumoto Kenji Ochiai Hisashi Takeuchi Ayako Fujitani

Kyoto University Manabu Kano Shinji Hasebe

Thank you for your attention. Any questions?

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