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5 MARCH 2020
Most Common Types of Observations in Regulatory Submissions of Chemical Characterization Results and How to Address Them...
Dr. Piet Christiaens
Content
• Short Introduction: The Nelson Discovery and Screener Database
• Errors in Chromatographic Screening for Extractables
• Addressing Regulatory Observations (through the use of a Database)
• Concluding Remarks
NELSON LABS UNIQUE SCREENER DATABASE
• Mainly built with Authentic Standards from detected/reported/publicly known Extractables
• Across ALL Materials of Construction (MoC)
• Total: >6500 Entries
• Population Distribution of the Database o 1000 Volatile Organic Compound (HS-GC/MS)
o 3500 Semi-Volatile Organic Compounds (GC/MS)
o 2000 Non-Volatile Organic Compounds (LC/MS)
• Analytical and Physicochemical Information per Compound /Analytical Mode o Mass Spectral Information
o Retention Time (RT-Lock)
o Relative Response Factors (RRF)
o Other Phycochemical Properties (LogP, Boiling Point,...)
CONFIRMED CONFIDENT TENTATIVE
80% 15% 5%
NELSON LABS UNIQUE SCREENER DATABASE
ERRORS IN CHROMATOGRAPHIC SCREENING FOR EXTRACTABLES
ERRORS IN ORGANIC EXTRACTABLES SCREENING
THE ERROR OF IDENTIFICATION
THE ERROR OF OMISSION
THE ERROR OF QUANTIFICATION
THE ERROR OF IMPLEMENTATION
ERRORS IN E&L SCREENING
THE ERROR OF OMISSION
INABILITY TO DETECT ALL EXTRACTABLES At or above a Justified Reporting (Safety) Threshold (eg AET)
CONSEQUENCE The undetected extractable cannot and will not be assessed
SEVERITY: FATAL ERROR The extraction profile is irriversibly compromised
Potential (toxic) compounds will be missed: wrong conclusion on Safety
1. Falling Through the Cracks
2. Failing to see a Tree in the Forest
TYPES OF OMISSION ERRORS
3. It never makes it off the column.
1. It never made it to the column in the first place.
1st Type of Omission Error: Falling Through the Cracks
2. Something unfortunate happens while its in the instrument.
4. Something unfortunate happens in the detector
2nd Type of Omission Error: Failing to see a Tree in the Forest
A DATABASE & REDUCING ERRORS OF OMISSION
By Injecting > 4,500 Authentic Standards, the responses for a large population of extractables are known for each technique
It is also known which compounds may be missed in a screening study (which compounds give no responses in either of the three Chromatographic techniques)
Database is based also on Material Composition Knowledge (eg literature, regulations, conference proceedings), not only on “What has been observed” in our own studies
Allows filling the gaps in Analytical Stategies for a Material/Device
The Database enables “TARGETED SCREENINGS”, minimizing the risk missing the
“trees in the forest”
THE ERROR OF IN-EXACT IDENTIFICATION
INABILITY TO IDENTIFY ALL EXTRACTABLES At or above a justified Reporting (Safety) Threshold (eg AET)
CONSEQUENCE No ability to link Compounds IDENTITY to associated TOXICOLOGICAL CONSEQUENCES
of that Identity
SEVERITY: FATAL ERROR In-exact Identification precludes a proper Safety Assessment
AET
DISCOVERED
RIGHT ID
WRONG ID
TOXICOLOGY
HN
OH3C
CH3
CH3
CH3
PDE, TI, ... Accute Systemic tox Carcinogenic tox Sensitizer, Irritant Reprotox ....
PDE, TI, ... Accute Systemic tox Carcinogenic tox... Sensitizer, Irritant Reprotox ....
O
O
A “Simple” Identification: “The Highest Match Score Wins!”*** Detected Compound
Acquired RT = 24.61 min
Best hit from
NIST/Wiley
INEXACT
IDENTIFICATION
1-aminocyclopentane-
carboxylic acid, N-
hexyloxy-carbonyl,
isohexyl ester
Library RT not available
Library Match = 80.7%
Best hit Nelson Labs DB
EXACT
IDENTIFICATION
1,1’-Carbonothioyl-
bispiperidine
Library RT = 24.58 min
Library Match = 98.4%
*** or even worse, “Any match score wins!”
TYPES OF IDENTIFICATION ERRORS: WRONG IDENTITY
The Highest Match Score Wins THE NELSON DATABASE
EXAMPLE
A RUBBER CURING ACCELERATOR
The “Home Court” Advantage
THE VARIOUS LEVELS OF IDENTIFICATION
+ Elemental Formula + Molecular Weight
+ Orthogonal Analytical Info
Structure elucidation
Confirmed with Authentic Standard (RT & MS)
Tentative + other supporting data
Increasing amount or rigor of
Confirmatory Information
Decreasing Certainty that the
Identification is Correct
General structure (e.g., phthalate)
Minimum identification level to
support a qualitative
toxicological safety assessment
(e.g., QSAR)
Minimum identification level
to support a definitive,
quantitative toxicological
safety assessment
HOW THE NELSON DATABASE REDUCES ERRORS OF MISIDENTIFICATION
All Entries in the Database that were Confirmed via the Analysis of Authentic Standards will lead to Unique Identifications and can be reported as CONFIRMED
Other Entries in the Database that were Not Confirmed via the Analysis of Authentic Standards will have undergone an extensive ID evaluation according to USP<1663> to rank them as either CONFIDENT or TENTATIVE
CONFIRMED in USP<1663>: “...The only means of providing a confirmed identification is via mass spectral and retention time match...”
With close to 6000 Compounds in our Database, we can offer UNIQUE Compound Identifications that will allow one to make the LINK between the Chemical Structure of the Extractable and its relevant Toxicological Information.
HOW THE NELSON DATABASE REDUCES ERRORS OF MISIDENTIFICATION
THE ERROR OF INACCURATE QUANTIFICATION
QUANTIFICATION OF EXTRACTABLES IS INSUFFICIENTLY ACCURATE
CONSEQUENCE The Assessment of Exposure of an Extractable to the Patient (eg through evaluation of
PDE’s) will be compromised and may lead to Flawed Conclusions
SEVERITY: CRITICAL ERROR A safety assessment can be performed, but the Inaccuracy of the Concentration/Dose
needs to be accounted for
[I.S.]known = 10 mg/L AreaIS = 100
Area[EXT] = 100
Assuming RFIS = RF [EXT]
I.S. EXT
Chromatogram of Extract
[EXT]Estimated = 10 mg/L
SIMPLE QUANTIFICATION
2 FATAL ERRORS HAVE BEEN
AVOIDED ALREADY
DISCOVERED
IDENTIFIED
I.S. EXT
[I.S.]known = 10 mg/L
Analysis of EXT Standard [EXT] = 10 ppm and [I.S.] = 10 ppm
Chromatogram of EXT STANDARD
[EXT]known = 10 mg/L Area[EXT] = 30
Area[I.S.] = 100
Relative Response Factor (RRF) EXT = 0,3
STEP 1 DETERMINE THE RRF FACTOR FOR THE EXT
COMPOUND
RELATIVE RESPONSE FACTOR (RRF) CORRECTED QUANTIFICATION
Relative Response Factor (RRF) EXT = 0,3
STEP 2 USE THE RRF FACTOR TO DETERMINE THE [EXT]
[I.S.]known = 10 mg/L AreaIS = 100
Area[EXT] = 100
I.S. EXT
Chromatogram of EXTRACT [EXT]Estimated = 33 mg/L
Authentic Standard Analysis of Over 4500 EXT with RRF are included in the NELSON LABS’ Database
RELATIVE RESPONSE FACTOR (RRF) CORRECTED QUANTIFICATION
HOW THE NELSON DATABASE REDUCES ERRORS OF INACCURATE QUANTIFICATION
The Relative Response Factor (RRF) information – per Technique – can be used in 2 ways:
2. The RRF’s in the database allow for INDIVIDUAL RRF correction, very valuable for LC/MS with a wide range of RRF distribution
1. At a minimum, the statistics on all RRF’s allow calculating an Uncertainty Factor for our methodologies
The Information of the Relative Response Factors of ALL 4.500 Authentic Standards that were injected allows screening in a quantitative way.
ADDRESSING REGULATORY OBSERVATIONS THROUGH THE USE OF A DATABASE
Observations from Authorities
Trying to avoid Making Errors (a.o. In Screening)
Article series: How a database can assist in reducing or eliminating errrors
in screening
How to use the Database in addressing regulatory
obervations
Only addressing observations regarding Analytical Testing Execution
• Discussion about the selection of the right detector for LC/MS (ESI vs APCI)
THE ERROR OF OMISSION
ESI APCI
Very Polar NVOCs
Ionized NVOCs
Low Polar NVOCs
Medium Polar NVOCs
Like Dissolves Like
UPW IPA & Hexane Hexane IPA UPW
NVOC Extractables
Unique to APCI
Respond to both APCI and ESI
Unique to ESI 25%
65%
10%
ADDRESSING REGULATORY OBSERVATIONS THROUGH THE USE OF A DATABASE
• The Nelson Database is more populated for
o APCI: 1200 Authentic Standards
o ESI: 350 Authentic Standards
o Historical Reason for Disproportion (PQRI)
• The ESI database is more requested for Chemical Characterization
• NELSON: Accelerated Efforts to Quickly Grow the ESI database
• As a consequence: the statistical evaluation may change over time...
• Provide ALL Library suggested identifications (NIST/WILEY)
• Do not Choose a structure from NIST/WILEY based upon the highest Match Factor
• When you select a compound from NIST/WILEY search, JUSTIFY
• All observed Extractables above the AET need to be Identified
• Compounds without CAS need further Identification
• If only a Partial Structure is available, report it as Unknown
THE ERROR OF MISIDENTIFICATION
• Provide ALL Library suggested identifications (NIST/WILEY)
• Do not Choose a structure from NIST/WILEY based upon the highest Match Factor
• All observed Extractables above the AET need to be Identified
• Compounds without CAS need further Identification
• If only a Partial Structure is available, report it as Unknown
THE ERROR OF MISIDENTIFICATION
• When you select a compound from NIST/WILEY search, JUSTIFY
• Optimize the CONFIRMED ID category through injection of Authentic Standards (>4,500 Compounds)
• Two dimensional confirmation of Retention Time and Mass Spectral Data • It waives all observations / requirements related to Identification through NIST/WILEY
Libraries
• There will still be a number of compounds that are not (yet) in the database • on average <1% HS-GC/MS; <10% GC/MS
• For the ID of these compounds, we partially rely on NIST/WILEY in GC/MS • The Observations / Requirements will apply for compounds Identified via NIST/WILEY
HOWEVER
THE ERROR OF MISIDENTIFICATION
• Provide ALL Library suggested identifications (NIST/WILEY)
• Do not Choose a structure from NIST/WILEY based upon the highest Match Factor
• Provide ALL Library suggested Identifications (NIST/WILEY)
• All observed Extractables above the AET need to be Identified
• Compounds without CAS need further Identification
• If only a Partial Structure is available, report it as Unknown
THE ERROR OF MISIDENTIFICATION
The need for High-End Analytical Equipment and Expertise (e.g. Accurate Mass MS-Platforms)
HAVE CAPACITY TO GO THE EXTRA MILE IN IDENTIFICATIONS
THE ERROR OF MISIDENTIFICATION
Unknown Observed
Use of High End Analytics
Identify Compound
Confirm ID Authentic Standard
Use ID in Next Study (Database)
• Liquid/Liquid Extractions: show data that final result is not underestimated
• Concentration step for IPA – HEX: Provide data that concentration of extracts does not result in Loss
• Provide literature evidence showing a single point calibration can be used to semi-quantify
• Justify the applicability of the used Uncertainty Factors (UF) based upon Lab or Method specific Basis
• When the Response Factor of a compound is unknown, avoid under-estimation by using a correction factor
• Provide data showing the analytical response variability is minimal for all compounds detected
• Include recovery information (surrogates) to verify the efficiency of the processing steps
THE ERROR OF INACCURATE QUANTIFICATION
Can (currently) be addressed with calculating the
UNCERTAINTY FACTORS (UF) based upon the Statistics of
the Database
Can be addressed through INDIVIDUAL CORRECTION of each
individual Compound in the Database
QUANTITATION ERRORS IN PERSPECTIVE
• Provide literature evidence showing a single point calibration can be used to semi-quantify
• Liquid/Liquid Extractions: show data that final result is not underestimated
THE ERROR OF INACCURATE QUANTIFICATION
• Concentration step for IPA – HEX: Provide data that concentration of extracts does not result in Loss
• Justify the applicability of the used Uncertainty Factors (UF) based upon Lab or Method specific Basis
• When the Response Factor of a compound is unknown, avoid under-estimation by using a correction factor
• Provide data showing the analytical response variability is minimal for all compounds detected
• Include recovery information (surrogates) to verify the efficiency of the processing steps
• Method Qualification should include multiple standards (3 for GC/MS, 5 for
LC/MS) at a range of Retention Times so that the Reporting Limit and
Dynamic Range is demonstrated for analytes with a variety of chemical
properties
• Provide Rationales for the LOD and LOQ for each analytical technique.
THE ERROR OF IMPLEMENTATION
CAS Compound Name Database RRF Response Function
RRF
Linear range Library RRF value /
Response Model RRF
% 583-39-1 2-Mercaptobenzothiazole* 0.112 0.535±0.038 2mg/L – 50mg/L 21
149-57-5 2-Ethylhexanoic acid 0.346 0.494±0.016 500µg/L – 50mg/L 70
5464-77-7 N,N-Dibenzylformamide 0.485 0.748±0.019 500µg/L – 50mg/L 87
112-52-7 1-Chlorododecane 0.568 0.856±0.026 50µg/L – 50 mg/L 66
104-76-7 2-Ethyl-1-Hexanol 0.515 0.518±0.020 50µg/L – 50 mg/L 99
112-12-9 2-Undecanone 0.627 0.692±0.030 50µg/L – 50 mg/L 91
122-39-4 Diphenylamine 0.834 0.938±0.021 50µg/L – 50 mg/L 89
593-49-7 n-Heptacosane 0.995 1.149±0.038 50µg/L – 50 mg/L 87
128-37-0 BHT 1.010 0.923±0.010 50µg/L – 50 mg/L 109
117-81-7 DEHP 1.010 1.104±0.027 50µg/L – 50 mg/L 91
31570-04-4 Irgafos 168 1.298 0.964±0.016 50µg/L – 50 mg/L 135
129-00-0 Pyrene 1.377 1.193±0.017 50µg/L – 50 mg/L 115
Average RRF accuracy (%): 93 ± 22%
Linear Dynamic Range: Depending upon the nature of the Compound
Limit of Detection (LOD): Depending upon the nature of the Compound
Limit of Quantification (LOQ): Depending upon the nature of the Compound
Typically 0,05 – 50 mg/L
Typically 0,02 mg/L
Typically 0,05 mg/L
Organic acids and amides (a.o.) may behave differently
CONCLUDING REMARKS
• The new ISO 10993-18:2020 Guidance has resulted in an increased level of Regulatory Questions
CONCLUDING REMARKS
• The Authorities and NB are on a learning curve – questions to understand the science and supporting information in a better way
• The best response to a regulatory question is the one you can avoid: explain in
report what you do, how you do it and why you are doing it
• Observed Trend: more questions about the Identification Process
• The NELSON database is instrumental in dealing with a broad set of regulatory observations
• However there is still an greater emphasis on the quantitative aspect of extractable testing
QUESTIONS?