Data Sharing Initiatives Dr Andy Teasdale

Transcription

1 Data Sharing Initiatives Dr Andy Teasdale PQRI/USP Workshop on Implementation Status of ICH Q3D Elemental Impurity Requirements - Analytical and Risk Assessment Challenges

2 Overview areas covered Why share data? What data already exists? How can this be augmented? What s the strategic intent of the database? Contributing data to the database / current status Vision for how the database could be used to facilitate risk assessments

3 Why Share Data? ICH Q3D is predicated on the evaluation of risk, this is made of 3 factors RISK = PROBABILITY x Severity x Detectability We know the severity Defined PDEs. We have detectability. DATA either newly generated or Historical data informs us as to the probability. Sharing data thus allows us to make informed judgement during the IDENTIFY and EVALUATE PHASES 3

4 Why Share Data? Q3D itself comments specifically on this: SECTION 5 - Information for this risk assessment includes but is not limited to: data generated by the applicant, information supplied by drug substance and/or excipient manufacturers and/or data available in published literature. SECTION 5.5. The data that support this risk assessment can come from a number of sources that include, but are not limited to: Prior knowledge; Published literature; Data generated from similar processes; Supplier information or data; Testing of the components of the drug product; Testing of the drug product. 4

5 Why Share Data? Q3D Case Studies use of first principles approach based on existing data exemplified. 5

6 What data already exists? How can this be augmented? Container Closure Systems THEORETICAL RISK Especially in the case of liquid formulations there is risk of metals leaching out of CCS into the formulation WHAT DOES THE DATA SAY? Materials in Manufacturing and Packaging Systems as Sources of Elemental Impurities in Packaged Drug Products: A Literature Review PDA J Pharm Sci Technol January/February :1-48; Section 5.3 Probability of elemental leaching into solid dosage forms is minimal and does not require further consideration in the risk assessment 6

7 What data already exists? How can this be augmented? EXCIPIENT STUDIES Study involved: Some 200+ samples Examined 24 elements Summary of results Little evidence of substantial levels of even the big 4/Class 1 (ubiquitous?) in mined excipients Pb seen in TiO2 but levels <10ppm, variability not significant. Pb also seen in Zn Stearate. Cd levels in Magnesium hydroxide / Calcium carbonate exceed Option 1 limits levels need to fail to an option 2 limit before serious concern 7 THIS IS 200 SAMPLES WHAT IF WE COULD COLLATE DATA FROM SAMPLES?

8 What data already exists? How can this be augmented? 8 Potential to facilitate more scientifically driven elemental impurities risk assessments and reduce unnecessary testing as part of the elemental impurities risk assessment efforts. The data to be shared is the analytical data generated to establish the levels of trace metals within batches of excipients used in the manufacture of pharmaceuticals.

9 What s the strategic intent of the database? Become the primary source of EI data for excipients that drives initial risk assessment (c.f. the Jenke paper for packaging components & EIs) Publish key findings with the intention of de-risking commonly used excipients Compare / contrast with data published generated by FDA. 9

10 Building the database How has the database been built? How much data is in it? Lhasa designed and developed the Elemental Impurities database based on VITIC TM platform Approved by the consortium in December 2015 Initial round of donations was received beginning of 2016 The database was first released at the end of March 2016 The Elementals database v contains the following number of records: 52 records in the Excipient table. 123 records in the Elementals table. 10 V just released now contains 157 excipients 757 result records

11 Building the database Procedure/process for organizations to share their in-house data Template defined to allow error free parsing of data. Data anomolised and checked by Lhasa. Data quality requirements Extensive discussions relating to data requirements Validation protocol generated 11 Extent of Validation recorded + Digestion Conditions No difference between data donated and data published in peer review journal in terms of vindication of data

12 Building a database Is all of the data for lactose and how will sufficient diversity of materials and suppliers be managed? The content of the database will be actively managed Clear commitment from members to generate data if gaps are identified Next data release will give a clearer picture to consortia members ListNo CarlMrozListName Total 1 Magnesium stearate 23 2 Microcrystalline cellulose 41 3 Lactose 32 4 Starch 14 5 Cellulose derivatives 18 6 Sucrose 9 7 Povidone 15 8 Stearic acid 3 9 Dibasic calcium phosphate Polyethylene glycol 6 Number of results

13 How is use of the database envisioned? At EMA meeting in April EFPIA presented a series of Case Studies The following slide examines how / where pre-existing data can facilitate the risk assessment 13

14 Oral Solid Dose Component Functionality Amount per 400 % in coated Type (Excipient) mg tablet (mg) tablet Core API Drug substance Hypromellose 2910 Binder Plant Microcrystalline Diluent Cellulose Plant Lactose Diluent Monohydrate Animal Crospovidone Disintegrant Synthetic Magnesium stearate Lubricant Mineral Coating Hypromellose 2910 Film-former Plant Titanium dioxide Pigment Mineral Triacetin Plasticiser Synthetic Blue Aluminium Lake Colorant # Mineral Blue Aluminium Lake Colorant # Mineral Several Excipients used in the formulated product. What data are available? Number of materials FDA External DB Internal Lactose 6 3 Hypromellose (not defined as 2910) MCC 14 6 Crospovidone 17 (povidone) Magnesium Stearate Titanium Dioxide 7 Blue Aluminium Lake #1 1 Blue Aluminium Lake #2 8 3 Database should contain substantively more data for common excipients Note Lactose is the main excipient others <10%

15 Excipient data Maximum level seen (ppm) Number of materials As Cd Hg Pb V Ni Co FDA Extern Intern FDA Extern Intern FDA Extern Intern FDA Extern Intern FDA Extern Intern FDA Extern Intern FDA Extern Intern FDA Extern Intern DB DB DB DB DB DB DB DB Lactose 6 3 <0.23 <0.03 <0.08 ND <0.5 ND <0.08 ND <2 ND <3 ND <0.8 ND Hypromellose < <0.1 0 < < ND <1 MCC 14 6 <1.0 ND <0.2 ND <0.5 ND <0.2 <0.1 <2 ND <3 <1 <0.8 ND 0.2 (actual number above LOQ) Crospovidone ND 0 ND 0 ND 0.06 ND 0.02 ND 0.1 ND 0.1 ND Magnesium Stearate Titanium Dioxide Blue Aluminium Lake # < <0.2 <0.1 0 <0.5 < <0.2 <0.1 0 < < <0.8 <1 0.5 (actual number above LOQ)

16 Excipient data Reflection on significance No appreciable traces of Class 1 or Class 2a elements in low risk excipients Lactose Povidone MCC Mg Stearate Ni seen at 1.5ppm NB less than 1% of the formulation Titanium dioxide 6ppm Pb / 6ppm V Is this significant? Component Functionality Amount % in coated Type (Excipient) per 400 mg tablet tablet (mg) Core Drug substance API Hypromellose 2910 Binder Plant Microcrystalline Diluent Cellulose Plant Diluent Lactose Monohydrate Animal Crospovidone Disintegrant Synthetic Lubricant Magnesium stearate Mineral Coating Hypromellose 2910 Film-former Plant Titanium dioxide Pigment Mineral Triacetin Plasticiser Synthetic Blue Aluminium Lake Colorant # Mineral Blue Aluminium Lake Colorant # Mineral

17 Excipient data Reflection on significance Component Category Quantity (mg/form) Dose "x" form (mg/day) Arsenic in component As ug in daily dose of Lead in component Pb ug in daily dose of ug/g formulation ug/g formulation Mercury in Hg ug in daily dose of component ug/g formulation Cadmium in Cd ug in daily dose of component ug/g formulation Vanadium in component ug/g V ug in daily dose of formulation Cobalt in component ug/g Co ug in daily dose of formulation Nickel in component Ni ug in daily dose of ug/g formulation x = 1 Total Bio Acc Total Bio Acc Total Bio Acc Total Bio Acc Total Bio Acc Total Bio Acc Total Bio Acc Total Bio Acc Total Bio Acc Total Bio Acc Total Bio Acc Total Bio Acc Total Bio Acc Total Bio Acc Dosage Form : Active Synthetic Hypomellose Synthetic MCC Plant derived Lactose Animal Crospovidone Synthetic TiO2 Mineral Mg Stearate Mineral Al Lake 1 Mineral Triacetin Synthetic Al Lake 2 Mineral Total Dosage Form weight Total element As Pb Hg Cd V Co Ni Permissible Limits As Pb Hg Cd V Co Ni Formulation Q3D Q3D Q3D Q3D Q3D Q3D Q3D Oral PDE Parenteral PDE inhaled PDE Based on data from database all predicted to be ~1% or less of PDE

18 Challenges to using first principles The data set is limited! - True but plan to develop a critical mass. Mined excipients will always show variability - Potentially true.. Component Dosage Form : Category Quantity (mg/form) Dose "x" form (mg/day) Arsenic in component ug/g As ug in daily dose of formulation Lead in component ug/g Pb ug in daily dose of formulation x = 1 Total Bio Acc Total Bio Acc Total Bio Acc Total Bio Acc Active Synthetic Hypomellose Synthetic MCC Plant derived Lactose Animal Crospovidone Synthetic TiO2 Mineral Mg Stearate Mineral Al Lake 1 Mineral Triacetin Synthetic Al Lake 2 Mineral How much impact would this have in the case of an excipient such as TiO2? 1000ppm Pb / Hg? Pb overall just exceeded RISK = PROBABILITY x Severity x Detectability Total Dosage Form weight Total element As Pb

19 Next Steps Hear more about the database - December 7 th Join Us! Contact : Crina.Heghes@lhasalimited.org

20 Conclusions The feasibility of sharing excipient elemental impurity data has been successfully demonstrated. Pooling and publishing data; Can surely help to improve the ease with which risk assessments can be completed Will give a much better picture of which materials represent a more significant risk than others Indicate where the risk is real & where it is negligible Reduce the amount of testing that is needed to be done moving forward to support implementation Confidentiality Notice This file is private and may contain confidential and proprietary information. If you have received this file in error, please notify us and remove it from your system and note that you must not copy, distribute or take any action in reliance on it. Any unauthorized use or disclosure of the contents of this file is not permitted and may be unlawful. AstraZeneca PLC, 1 Francis Crick Avenue, Cambridge Biomedical Campus, Cambridge, CB2 0AA, UK, T: +44(0) , 20