1. High Resolution FT-MRR Spectroscopy: Trace Residual Impurities Analysis Without Chromatography
Brent J. Harris, Shelby S. Fields, Justin L. Neill, Robin L. Pulliam, Matt T. Muckle
BrightSpec, Inc., 770 Harris St. Suite 104b, Charlottesville, VA, USA.
Brooks H. Pate
Department of Chemistry, University of Virginia, McCormick Road, Charlottesville, VA, USA.
Hi, my name is Shelby Fields and I’ve had the pleasure of working on method and sampling development at Brightspec for the past year since receiving my undergraduate degree from the University of Virginia in At Brightspec, we have two main missions
Find long lasting, unsolved, and painful analytical challenges
Make rotational spectrosocpy a lab, household name by utilizing the latest advances in technology
ISMS 2016
© 2016 BrightSpec, Inc.

2. Analytical Chemistry Tools
Pervasive challenge - dealing with gaps between instrumentation capabilities
Spectroscopy
+ Simple, non-destructive
+ High degree of automation
+ Molecular specificity
selectivity in complex mixtures (dynamic range)
Chromatography
+ High selectivity and applicability
+ Low detection limits
High degree of customization
Complex methods
Identification ambiguity
This is perhaps oversimplified perception of analytical instrumentation to an industry chemist. Where spectroscopy can provide very precise measurement with easy sampling, it
Can sometimes fall short when analyzing complex mixtures. Where Chromatography is a great tool for these mixtures, significant method development is often required for accurate
Analysis. At Brightspec we aim to find easy solutions to these industrial challenges using FT-MRR spectroscopy.
Use FT-MRR to pull more analyses into the “easy” category
Where’s the detector?
ISMS 2016
© 2016 BrightSpec, Inc.

3. The FT-MRR detector BrightSpec One 260-290 GHz Spectrometer
“A Segmented Chirped-Pulse Fourier Transform MM-Wave Spectrometer ( GHz) With Real-Time Signaling Averaging Capability (WH13)”
Brent J. Harris et. Al, ISMS 2013
GHz (Justin Neill FC10)
30 mW power source Segmented CP-FT
2 ms acquisition sequence
Edgar instrument control software – experiment customization
The Brightspec ONE GHz segmented chirped pulse Fourier transform spectrometer was the instrument used for experimentation. While we used exclusively this frequency band for experimentation, at Brightspec we employ a number of others. For more information on band comparisons, see Justin Neill’s talk, FC10. This instrument is a more industry-ready version of that pictured here, which was presented upon at ISMS Brightspec One is controlled by Edgar instrument control software, which allows for experiment customization and analysis using an extensive finger print library and matching algorithm.
Lineage from Segmented CP-FT
Frequency bands (reference Justin’s talk)
Instrument and software
tech friendly, plugs in mains power, a lot of automation, < 100 lbs, software controlled
Now for the sampling..
ISMS 2016
© 2016 BrightSpec, Inc.

4. The Sampling - Static Headspace
Residual solvent
5 minute cycle time
10 – 100 ppm detection limit
Genotoxic impurity
10 minute cycle time
10 – 100 ppb detection limit
And so, we have the detector. Now we need find one of those analytical challenges and pull it to the easy column …
If you want to find an urgent problem, then you need to work on someone’s product/material …that means headspace (gas)
For this work, we are focusing on pharmacetuicals … two main analytical applications are residual solvent and genotoxic impurity analysis. Diagramed above
Are our standard headspace sampling methods, and their associated cycle time and sensitivity limits necessary for industry adoption.
ISMS 2016
© 2016 BrightSpec, Inc.

5. Real World Application of Thermal Evolution
Acetamide: An Ideal candidate for FT-MRR detection, difficult to sample
Molecular weight of < 100 amu
Strong dipole moment > 1 Debye
Conformational Rigid Yes
Vapor pressure < 1 Torr at 40 C
Genotoxic Impurity Yes
We picked acetamide. Acetamide is a good candidate for FT-MRR detection for a number of reasons. It has a low atomic mass (less than 100 amu), a non-zero dipole moment, and is confirmationally rigid so it’s Boltzmann curve is well populated and dense in our chosen frequency range. It is considered a genotoxic impurity, so the pharmaceutical industry is interested
In it’s analysis. The vapor pressure is less than 1 Torr at 40C, hence why the industry considers this analysis difficult. This means that our headspace method may require some additional development.
Next, we need to set goals..
ISMS 2016
© 2016 BrightSpec, Inc.

6. Experimental Goals Reference spectra measurement Unlimited sample
Pure acetamide finger print
Associate signal with pressure (quantitate without generating Hamiltonian fit)
Real sample measurement
Static measurement – limited sample available
Realistic API (Active Pharmaceutical Ingredient) matrix
Our first goal in this experiment is to measure a pure acetamide reference spectra. We will have unlimited sample, so we can perform a flow cell measurement. The ultimate goal here is to tie a signal with a partial pressure, so that we can quantitate without a Hamiltonian fit. The next objective is to measure acetamide in a realistic API, or active pharmaceutical ingredient. In a realistic scenario, a limited supply of sample will be available, so this measurement will have to be done statically.
Lets see what happens..
ISMS 2016
© 2016 BrightSpec, Inc.

7. Challenge: Acetic Acid
Spec.
Sample
17:1 S:N, 1 mTorr, 10 min
So we started simple. We place some aceatamide in a vial, and connected it directly to the spectrometer. The above spectra was measured. As you can see, there is some acetamide in the chamber, but the spectra is dominated by acetic acid, which is likely a residual solvent. It is easy to see why this is the case when the vapor pressures of the two molecules are compared. Acetic acid has over 35 times more vapor pressure than acetamide, and so it dominates the headspace above the sample. During this first shot, more challenges were discovered..
Static headspace analysis resulted in measurement of nearly pure acetic acid spectra
Acetic acid Torr
vs.
Acetamide < 1 Torr
Vapor pressure at 40 C {
Even more challenges!
ISMS 2016
© 2016 BrightSpec, Inc.

8. Challenge: Condensation
At TRM , solids condense in transfer lines and sample cell
Chart of signal intensity vs. time of static acetamide (after flow cell measurement)
At room T, solids condense in sample transfer lines and on the wall of the cell, and can appear as contamination in subsequent measurements. To the left is a series of overlaid spectra measured periodically on a static cell over 12 minutes following our simple acetamide experiment. Clearly, some method development is necessary to measure clean, repeatable spectra.
Multiple overlaid spectra cataloging static acetamide signal over the course of 12 minutes
Acetamide condensing on walls of sample cell
We need solutions..
ISMS 2016
© 2016 BrightSpec, Inc.

9. Apparatus/Method Criteria
Challenges
Solutions
Competing with high volatility impurities for headspace
Condensation (poor transfer efficiency)
Sublimation on glassware
Materials – PFA tubing
Nitrogen flow
Flow and static measurements
So here we have our challenges. We need some way to purify our acetamide, for a pure spectra, and we need some way of cleaning the spectrometer between measurements. Here are the solutions that were designed into the apparatus and method to meet these challenges. For purification, we added glassware for sublimation. To reduce carryover, we made the system primarily of PFA tubing, and added a nitrogen flow to flush out condensation. In addition, the apparatus was designed so that it could accommodate both flow and static measurements.
ISMS 2016
© 2016 BrightSpec, Inc.

10. Method (Flow) Acetamide into glassware, then seal
Sublimation at 80 C, recrystallization on TRM glassware walls
Reheat glass walls (crystal volatilization)
Start nitrogen flow (0.2 sccm determined to be optimal for this experiment)
Open acetamide headspace
Measure
To Sample Cell
(1930 mL)
Sample Loop (5.2mL)
Nitrogen Flow
(0.2 – 2.0 sccm)
Solid
Heat
Diagram of loop transfer apparatus used for acetamide experimentation
This was the procedure ultimately used for our flow cell reference measurement. As you can see it involved two sublimations at 80 C, and a nitrogen flow. This flow was important as it encouraged acetamide vapor into the sample cell. Different flows work better for different molecules. In our case, 0.2 sccm was determined to be optimal.
ISMS 2016
© 2016 BrightSpec, Inc.

11. Acetamide Reference What about static?
170:1 S:N, 0.08 mTorr (2.16 mTorr total), 10 minutes
Acetamide reference flow spectra measured on BrightSpec ONE
Thermal Evolution sampling resulted in pure acetamide spectra (comparison with literature data)
Measurement with cell at 40 C, sublimation at 80 C
Nitrogen flow of 0.2 sccm resulted in sample pressure of 0.08 mTorr – 1.52 mV/mTorr
Acetic acid spectral signature not encountered by Edgar matching algorithm
This spectra was measured using the flow procedure. As you can see, acetic acid wasn’t detected by the Edgar matching algorithm. A signal: sample pressure ratio was found to be 1.52 mV/mTorr using this spectrum. So we have our reference, now we need to establish a procedure for realistic measurements.
What about static?
ISMS 2016
© 2016 BrightSpec, Inc.

12. Loop Transfer
In realistic measurement, limited supply of sample available
Generally – three types of headspace sampling methods
Gas-Tight Syringe Injection
Balanced – Pressure System
Loop Transfer
To Sample Cell
(1930 mL)
Sample Loop (5.2mL)
Nitrogen Flow
(0.2 – 2.0 sccm)
Solid
Heat
Constant volume loop allows for static measurements
Generally, analytical chemists rely on one of three techniques for headspace sampling. The Gas-Tight syringe Injection, Balanced-Pressure System, or Loop transfer method. In our case, we designed our apparatus to accommodate a loop transfer. We used this fixed volume loop to dump consistent amounts of sample into the sample cell. This provided a feasible method for static measurements, which are preferred when limited sample is available. Now all we need is an API..
Realistic API?
ISMS 2016
© 2016 BrightSpec, Inc.

13. Acetaminophen 0.5 wt % acetamide in acetaminophen
Common pharmaceutical API
0.5 wt % acetamide in acetaminophen
50mg used for API experimentation
Ground using mortar and pestle
For our API we chose Acetaminophen, an over the counter, common pharmaceutical drug. We used a mortar and pestle to grind up a 0.5 wt/wt % mixture of acetamide in acetaminophen. 50 mg of this sample was used for experimentation.
ISMS 2016
© 2016 BrightSpec, Inc.

14. Method (Static) Acetamide into glassware
Sublimation at 80 C (144 C), recrystallization on TRM glassware walls (under vacuum)
Reheat glass walls (crystal volatilization)
Open acetamide Sample Loop for 30 seconds, then close loop
Open Sample Loop to cell for 30 seconds, then close cell
Measure
To Sample Cell
(1930 mL)
Sample Loop (5.2mL)
Nitrogen Flow
(0.2 – 2.0 sccm)
Solid
Heat
This was the procedure followed for static measurements. As you can see, it once again entails two sublimations. Instead of a flow measurement, however, a 30 second loop load followed by a 30 second loop dump was utilized. Nitrogen was flowed through the cell until a clean blank was measured between trials.
ISMS 2016
© 2016 BrightSpec, Inc.

15. Results (80°C, Tmelt Acetamide)
Static measurement of 1 mTorr of 50 mg of 0.5 wt % acetamide
spiked acetaminophen heated to 80 C (melting point of acetamide)
12:1, 1 mTorr, 1.5 minutes
Signal around 0.01 mV
No acetaminophen/other impurities detected
Method – sample transfer efficiency of 0.15%
The first measurement was made with sublimation at 80 C, the melting point of acetamide. As you can see, we observed an acetamide signal of around 0.01 mV, and no acetic acid signal. Based on this signal, we observed a transfer efficiency of 0.15%.
ISMS 2016
© 2016 BrightSpec, Inc.

16. Results (144°C, Tmelt Everything)
Spectra analyzed using Edgar matching algorithm
Many residuals detected
Acetamide spectra identified with signal intensity similar to 80 C (0.01mV)
We then performed another trial, this time with a sublimation at 144C, the melting temperature of the sample. This time a number of residuals were detected by the Edgar matching algorithm. Importantly, acetamide was detected at 0.01 mV once again, a signal comparable to the previous 80C trial.
50:1 Dynamic range, 1 mTorr, 1.5 minutes
Inserts below spectra are narrow bandwidth view illustrating detection of acetic acid and acetaldehyde at signal:noise ratios of 3:1
Acetic acid Acetaldehyde
ISMS 2016
© 2016 BrightSpec, Inc.

17. Conclusions
Thermal Evolution (sublimation) Technique along with Nitrogen flow resulted in successful measurement of pure acetamide spectra with associated pressure
Signal - .12mV, pressure – 0.08 mTorr
Signal/Sample pressure – 1.52mV/mTorr
Thermal Evolution method utilized for loop transfer
0.15% efficient headspace transfer
Acetamide successfully measured as genotoxic impurity in realistic matrix
80°C- measured as sole volatilized analyte
144°C- measured along with numerous residuals
Both spectra- observed with signal strength of 0.01mV
So, did we meet our goals? We successfully observed a pure acetamide reference spectra by sublimating our solid sample, and then gently flowing nitrogen through the flow cell. Using this reference spectrum we observed a signal/sample pressure ratio of 1.52mTorr/mV. We then adapted this sublimation to our loop transfer. Our method yielded a transfer efficiency of 0.15%. We successfully measured acetamide mixed into a realistic API matrix. At 80C, it was measured as the sole volatilized analyte, while at 144C it was measured along with other residuals. At both temperatures the acetamide signal was 0.01mV.
ISMS 2016
© 2016 BrightSpec, Inc.

18. Further Experimentation
Quantitation – Use of expansive spectral library and Edgar matching algorithm for compositional analysis of unknown mixtures
Reduced cycle time – cutting down established procedures for measurement while maintaining accuracy
More realistic experimental matrix – subject analytes imbedded in API matrix for more realistic measurement conditions
Further, the ultimate goal is repeatable quantitation of unknown mixtures using the Edgar matching algorithm and finger print library. We would like to reduce the cycle time necessary of static measurements while maintaining our precision. And finally, we would like to perform similar tests using a sample that is actually imbedded in an API matrix, instead of mixing one our selves.
ISMS 2016
© 2016 BrightSpec, Inc.

19. Thank You FT-MRR for Analytical Chemistry … … and Scientific Discovery
BrightSpec Inc. Charlottesville, VA
Instrument Sales, Trials, Demos
Method Development
Analytical Services
770 Harris St. #104b | Charlottesville, VA 22963
ISMS 2016
© 2016 BrightSpec, Inc.

20. Nitrogen Flow
N2 Flow (Sccm)
N2 Pressure (mTorr)
Total Pressure (mTorr)
Sample Pressure (mTorr)
Signal (mV)
Signal/Sample Pressure(mV/mTorr)
0.0
0.00
0.26
0.2834
1.09
0.2
2.08
2.16
0.08
0.1212
1.52
0.5
3.65
3.17
0.09
0.082
0.84
1.0
6.18
6.30
0.12
0.0492
0.41
Sublimate sealed solid
Open nitrogen flow to cell (allow pressure to equilibrate)
Open sublimated solid to cell (allow pressure to equilibrate)
Measure
ISMS 2016
© 2016 BrightSpec, Inc.

21. Detection Limit Calculation
250 mg available (4.2 mmol)
65 mL (glassware and loop) at 80 C produces 1.9 Torr
1900 mL (Loop and Sample Cell)
___________________
= 380
5mL (Loop Size)
1.9 Torr
380
= 5 mTorr
______
With Temperature reduction = 4.4 mTorr
0.007 (mTorr transferred)
__________________
= 0.16% transfer efficiency
4.4 (mTorr theoretical)
ISMS 2016
© 2016 BrightSpec, Inc.

22. Detection Limit Improvement
All PFA, heated transfer lines with calibrated loop transfer results in higher signals.
With targeted mode analysis 1.3ppm detection limit possible
0.23 mV broadband signal predicted – 20% sample transfer efficiency ~
ISMS 2016
© 2016 BrightSpec, Inc.

23. Detection Limits
Thermal evolution from dry powders – development goals:
< 1 ppm detection limits
Oxygen starved heating
Truly direct, investigative analysis
Residual solvent - measured detection limits:
Isopropanol (< 10 ppm)
Dichloromethane (< 10 ppm)
Diethyl Ether (< 10 ppm)  library match by simulation
Isobutylene (< 10 ppm)  ID initially by structure intuition, the add to library
Acetaldehyde (< ppm)
Formaldehyde (< ppm)
Sulfur Dioxide (< 10 ppm)
Hydrogen cyanide (< ppm)
ISMS 2016
© 2016 BrightSpec, Inc.