1.
Out of the shadows:
Hunting for common impurities in
cannabis products
Dr. Eric Janusson, Dr. Markus Roggen

2.
Introduction
DELIC Labs is a research venture that seeks to add fundamental scientific
insight to the field of cannabis and mushroom production.
We seek to support the cannabis and mushroom industries by
establishing a centralized hub in Vancouver, BC, for collaborative
research focused on:
• Process Design
• Process Optimization
• Process Analytics
• Formulation Research

3.
Collaborative Research
DELIC Labs collaborates with academic, industry and private groups
around the globe. Some highlights of those collaborations are:
• University of British Columbia, Vancouver
• Loyalist College, Belleville
• Via Innovations by Dr. Monica Vialpando
• Veridient Science by Dr. Linda Klumpers
Fundamental Collaboration

4.
Research Topics
• Chemometrics and data analytics for process control and optimization
• Kinetic studies to understand mechanisms
• In-process analytics for process control
• Computational studies to understand mechanisms
• Process development, like crystallization
Fundamental Cannabis and Mushroom Chemistry

5.
State of the Art
Quantitative analytical methods
for cannabinoids exist
• Industry still growing and
requires development
Challenges:
• Sample matrix complexity
• Mathematical and method
errors
• Unknown byproducts and
contamination
5

6.
Outline
1) Full characterization of synthetic byproduct (HHC)
2) Discovering new compounds with advanced MS techniques
6

7.
Identification of HHC
Hexahydrocannabinol as byproduct in Cannabinol production
7

8.
8
• CBN is a sought-after cannabinoid
• Produced by oxidation of THC
• Major Methods:
• I2-Oxidation
• Pd-Oxidation
• Forgotten stash
• HHC (reduced THC) is the new kid on the block
CBN Production Byproducts
I2: 10.1021/acs.jnatprod.7b00946

9.
9
• Palladium-catalyzed oxidation of THC to CBN leads to byproducts
When THC Oxidation goes the Wrong Way

10.
10
• Two major byproducts have identical mass of 316.2 Da
When THC Oxidation goes the Wrong Way

11.
11
• Isolate the twin peaks at 9.5 min
• Hexane/Ethyl Acetate in 20/1 ratio
• Classic silica gel column
What are those Two New Peaks

12.
12
• Important peaks for THC and CBN to remember
Reference NMR for Identification
wide spectrum of cannabinoids naturally occurring in
noids refers to terpeno-phenolic C21 and C22 compounds
hemp plant. They are predominantly formed in the
p plant [6,7]. The occurrence of a carboxyl group allows
ses: cannabinoid acids featuring a carboxyl group (e.g.,
HCA) and cannabidiolic acid (CBDA)) and the neutral
rent cannabinoids and their carboxylic acid analogs and
in the literature [8]. The individual cannabinoids differ
The modifications are mainly limited to changes of the
ydrocannabivarin (THCV), in Figure 1), the substitution
oup, or an additional cyclization [9].
ing so-called full spectrum hemp extracts is not CBD-se-
wide spectrum of cannabinoids naturally occurring in the
nnabinoids refers to terpeno-phenolic C21 and C22 com-
nd in the hemp plant. They are predominantly formed in
le hemp plant [6,7]. The occurrence of a carboxyl group
two subclasses: cannabinoid acids featuring a carboxyl
inolic acid (THCA) and cannabidiolic acid (CBDA)) and
than 120 different cannabinoids and their carboxylic acid
s are described in the literature [8]. The individual canna-
heir structures. The modifications are mainly limited to
ain (e.g., ∆9-tetrahydrocannabivarin (THCV), in Figure 1),
acid or hydroxyl group, or an additional cyclization [9].
d in this work including the applied numbering system. (a)
); (b) R = H: ∆9-tetrahydrocannabinol (∆9-THC), R = COOH:
nabinol (∆8-THC); (d) cannabinol (CBN); (e) ∆9-tetrahydro-
in this work including the applied numbering system.
CBDA); (b) R = H: D9-tetrahydrocannabinol (D9-THC),
etrahydrocannabinol (D8-THC); (d) cannabinol (CBN);
Toxics 2021, 9, 136 10 of 20
Toxics 2021, 9, x 10 of 20
Figure 2. 1H NMR spectra of cannabinoids CBD, CBDA, CBN, CBG, ∆9-THC, THCA, ∆8-THC, THCV dissolved in CDCl3.
* Cannabinoid stabilized as N,N-dicyclohexylammonium salt.
Figure 2. 1H NMR spectra of cannabinoids CBD, CBDA, CBN, CBG, D9-THC, THCA, D8-THC, THCV dissolved in CDCl3.
* Cannabinoid stabilized as N,N-dicyclohexylammonium salt.
10.3390/toxics9060136
OH
O
1
2
4
5 6
7
9
10
3’
5’ 1’’
2’’
3’’
4’’
5’’

13.
13
• Only two protons in the aromatic region
• No signal for double bond
• Pair of broad doublets in a 2 to 1 ratio near H-1 of THC
1H-NMR of both Compounds!
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
2.2
2.4
2.6
2.8
3.0
3.2
3.4
3.6
3.8
4.0
4.2
4.4
4.6
4.8
5.0
5.2
5.4
5.6
5.8
6.0
6.2
6.4
6.6
6.8
7.0
f1 (ppm)
rd-03.1.fid
ubc_1H CDCl3 {C:Brukertopspin2.1} gsammis 40
6.26
2.47
5.93
7.31
3.83
6.12
1.62
3.05
0.31
0.74
0.90
1.00
0.99
0.87
0.89
0.91
0.94
0.96
1.08
1.13
1.15
1.29
1.30
1.31
1.38
1.53
1.56
1.61
1.65
1.83
1.87
2.88
2.92
3.04
3.08
6.08
6.26

14.
14
• Looks like single compound!
• Doublets in a 2:1 ratio -> two diastereomers
• No unsaturation in limonene moiety
1H-NMR of both Compounds!
3’
5’
1a 1b
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
2.2
2.4
2.6
2.8
3.0
3.2
3.4
3.6
3.8
4.0
4.2
4.4
4.6
4.8
5.0
5.2
5.4
5.6
5.8
6.0
6.2
6.4
6.6
6.8
7.0
f1 (ppm)
rd-03.1.fid
ubc_1H CDCl3 {C:Brukertopspin2.1} gsammis 40
6.26
2.47
5.93
7.31
3.83
6.12
1.62
3.05
0.31
0.74
0.90
1.00
0.99
0.87
0.89
0.91
0.94
0.96
1.08
1.13
1.15
1.29
1.30
1.31
1.38
1.53
1.56
1.61
1.65
1.83
1.87
2.88
2.92
3.04
3.08
6.08
6.26
OH
O
1
2
4
5 6
7
9
10
3’
5’ 1’’
2’’
3’’
4’’
5’’

15.
15
GCMS conditions:
• GC: Agilent Intuvo 9000 GC
• MS: Agilent 5975 MSD
• Column: Agilent HP-5MS UI
(30 m x 250 um x 0.25 um)
• Carrier gas: He, 1.0 mL/min
DIY Detection of HHC by GCMS
Ramp Rate
(˚C/min)
Temp (˚C) Hold Time
(mins)
Run Time
(mins)
Start • 60 1 1
1 1.5 60 1 2
2 1.5 80 1 16.3
3 10 130 1 22.3
4 5 175 5 36.3
5 10 275 10 56.3

16.
MS Analysis
Strategies for exploring the unknown
16

17.
17
Preprocessing:
database
construction
Demultiplex
experiment
DIA data
ML-assisted
annotation
Ontological
classification
Substructure
pairing
Spectral
networking
Substructure
grouping
MS Analysis Pipeline

18.
18
• Spectral deconvolution of DIA data facilitates identification
Cannabis Sativa Extract QTOF MS
0.0 2.5 5.0 7.5 10.0 12.5 15.0 17.5 20.0 Time [min]
0.0
0.5
1.0
1.5
6
x10
Intens.
RP-HPLC-ESI(+)MS
BPC
Linear gradient elution
(MeOH/H2O, 0.1% FA)
98.5126
144.0816
323.1613
EJ133_HLgradient_P1-B-2_01_16176.d: +MS, 4.0-4.3min #1050-1107
0.0
0.5
1.0
1.5
2.0
5
x10
Intens.
100 150 200 250 300 350 m/z
> 2000 unknown compounds
?

19.
19
MSMS Pattern-Database Similarity
MSMS annotation requires similarity metric:
1. Query database with experimental
fragmentation pattern
2. Compare spectral features
3. Measure similarity. Do they match?
Modified cosine score considers m/z deltas
(shift mass)
• Compensation for functionalization and
ESI adducts
Modified Cosine Scores for MSMS Library

20.
20
“Intelligent” Database Comparisons
• Annotation using a
heuristic machine learning
algorithm
• Spectral patterns treated
like words
• Contextual comparisons
(semantic similarity)
• Computationally
scalable
F. Huber, et. al., PLoS Comput. Biol., 2021
‘Intelligent’
contaminant
filtration

21.
21
Molecular Networking
Jeramie Watrous, Pieter C. Dorrestein, et al. PNAS 2012
• Experimental and
reference MSMS
spectra
compared to
each other
• Spectral similarity
can be
determined
between samples

22.
22
Beneath the Surface
What about the
uncommon
molecules?
Terpenes Cannabinoids
Entourage
Effect
Munchies
Flavonoids
Thiols
Dimeric
cannabinoids
Sugars
Metals
Molecular network of structurally similar
compounds in Cannabis Sativa extracts

23.
Cannabis Extract Characterization
Name
Signal
Counts
Cannabidiol 460391.98
Hydroxyphenyllactic Acid 453878.6
2-Oxoadipate 444552.98
Delta9-THC 365064.34
Ferulic acid 364440.9
Citric acid 344519
N-acetyl-2-
phenylethylamine 341646.6
Azelaic Acid 335584.7
Cannabigerol 302547.09
Glabridin 299706.87
Aconitic Acid 273323.42
Diacetyl 264227.6
Cysteine 260575.5
High-abundance compounds detected by
LCMS in Cannabis Sativa extracts
. . .
Mass-shift pairs in cannabis sativa
extract

24.
CRM marker
assistance
promotes
compound
discovery
24
∆9-THC
Finding Cannabinoid-like Molecules

25.
25
Sample preparation is challenging
• Matrix interference
• Inter-cultivar variation
• Obtaining a representative dataset
• What is an ‘average’ sample?
What can we do?
• Cryogenic flower ‘embrittling’
• Spike workflow stages
• Instrument optimization
Next Steps for
Cannabis Analysis
A network of suspected and known contaminants in Cannabis Sativa
extract
PULVERISETTE 0
Vibratory Cryomill

26.
Thank you! Questions?