1. Advances in Microsampling and Considerations for Interpretation of Results
Kenneth Lewis, Ph.D.
OpAns, LLC
RTP, NC

2. Outline History of Microsampling Challenges of Microsampling
Matrix Differences and When They Matter
Example Bridging Study
Interpretation for Drugs
Interpretation for Steroids
Interpretation for Chemistries
Conclusions

3. History

4. What is Microsampling
Microsampling is the collection of low volume samples by non- invasive means
Includes
Dried Blood Spots
Dried Urine
Low volume Saliva
Low volume hair sampling
Sweat sampling
“Painless” non-venipuncture collection of <200 microliters of blood
Used to
improve patient comfort
reduce sample handling at collection
improve sample stability
reduce transit expense.

5. Bacillus Subtilis halo Guthrie testHO
1934
PAH
Borgny Egeland
1984
Ashbjorn Folling, 1962
Bacillus Subtilis halo
Guthrie test

6. Bacillus Subtilis halo Guthrie testHO
1934
PAH
Borgny Egeland
1984
Siblings – 11 & 2 ½
Mid 1960s
Asbjorn Folling, 1962
Bacillus Subtilis halo
Guthrie test

7. Newborn Screening Moves to Mass Spec
David Millington, PhD Professor Emeritus at Duke University is the father of modern newborn screening by mass spectrometry
Transition to Mass Spectrometry Enabled
Multiplexed characterization of inborn errors of metabolism
Lower sample volumes (fewer spots)
Better sensitivity and specificity (near 100%)
A large market enabled
Advancement in analytical methodology
Advancement in automation
Reduction in cost
The result has been a drastic reduction in symptoms, a healthier population, and less cost to society.

8. Guidance on Card Specifications

9. 21st Century – Pharma Drives Innovation
Pharma advances microsampling to reduce animal use in pre- clinical and facilitate patient testing at home and remotely
Volume reduction allows for sequential testing from mice
Important for xenographs
Reduces the number of animals needed for a study
Serial sampling produces better data
Reduces animal cost, but not necessarily study cost.
At home testing is essential for certain conditions e.g. seizures
Capillary testing is essential for remote testing from babies.
Capillary testing for rare/remote diseases

10. 21st Century – Payers want Cost Reduction
Venous collection of blood samples is expensive
Need for specialized personnel - phlebotomist
Need for dedicated facilities – draw stations, centrifuges, refrigerators
Expensive logistics – cold chain shipping
Reduces animal cost, but not necessarily study cost.
Miniturization in lab uses less reagent
Microfluidics hold the promise of
Highly automated
Low cost of reagents
Small footprint
Faster analysis times
Challenge is coupling our macro world with micro analysis
Success and Failure
Theranos
Baebies
Improved Patient Experience is nice

11. 21st Century – Patients want Access
Health insurance shift to high deductible/patient responsibility is resulting in a return to consumer awareness.
Personalized medicine is driving longitudinal testing
Social media/internet is driving education for motivated patients/advocates resulting in a desire to “know”
Resulted in a significant growth of independent labs

12. Challenges of Microsampling

13. Challenges: Proper Spotting
Spot Volume impacts sampling volume
Amount on top of paper
Depth of penetration
Width of penetration
Hematocrit and Paper impact sampling volume
Tools
Nothing
Capillaries
Drummond pipette
Internal Standards
Training
Can be done with clinical trials
Rarely practical with clinical diagnostics

14. Example DBS Cards (from one site in the same shipment)
Barcode
Barcode
Barcode

15. Example DBS Cards (The problems occur at collection)
Barcode
Barcode
Barcode
Barcode
Barcode
Barcode
Barcode
Barcode
Barcode

16. Challenges: Training Need for a volumetric transfer device (capillary)
Incorrect spot volume
Blood clots
Incorrect location on card
Failure to dry the card
Place card in separate bag from desiccant
Spot Humidity Indicating Card
Surface contamination
“Only two things are infinite, the universe and human stupidity, and I am not sure about the former.” – Albert Einstein

17. Card Options (Can we find a better card?)
Barcode

18. A Better Card Collection Funnel directs blood and protects top of card
Individually Labeled
Visual indicator of collected volume
Instructions on the card
Back layer prevents contamination
Absorbent layer is undisturbed
Absorbent layer can be any material
Tear-off tracking tags for inclusion in files or given to patients

19. Matrix Differences and When They Matter

20. Matrix Types Venous Capillary Urine Saliva Hair
Whole Blood
Plasma
Serum
Subfractions (e.g. PBMCs)
Capillary
Urine
Saliva
Hair
Rare (CSF, Semen, Tears, Sweat etc.)

21. Distribution
The pharmacology concept of Distribution must be applied to both the sample type and analyte being measured.

22. Example Bridging Study

23. Government’s Approach to Improve Pediatric Treatment

24. How Did the PTN Start?
“Create an infrastructure for investigators to conduct trials that improve pediatric labeling and child health.”
Sponsored by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)
Network for studying drug product formulation, age-appropriate drug dosing, efficacy, safety, and device validation
Primary management by Duke Clinical Research Institute (
Collaboration: Duke, Children’s Mercy Hospital, UCSD, UNC, CNMC, CHOP, and 100 clinical sites
Primarily PK/PD and safety trials
Success: Completed trials that improve dosing, safety information, labeling, and ultimately child health

25. PTN Site Network
Plus:
Alaska, Hawaii, Singapore

26. Methods Concept : Why? Insanity is doing the same thing, expecting different results
Short version of drug development in the nursery— use products repeatedly, complain that drug companies don’t study the products, and continue to use products for decades until the next product comes along. Repeat.
Patient has a rare problem and needs a drug almost never used in the NICU. Guess at the dose. Repeat.
Try something new.

27. Methods Concept: Opportunistic Design
Inclusion Criteria: Infants who are receiving understudied drugs of interest per standard of care as prescribed by their treating caregiver Exclusion Criteria: Failure to obtain consent Dosing information, safety data, samples, and (potentially) PD marker if enough infants are enrolled
PK sampling times: pre- specified by dosing interval
Obtain key time points
Have the option to modify time points via conference call with the investigators once enough infants have been enrolled

28. Methods Concept: Scavenge Sampling
A sampling strategy whereby blood is “scavenged” from samples that otherwise go into the trash
Every day, premature infants have routine labs (variable by site) for chemistry (parenteral nutrition), etc.
E.g., the nurse may obtain samples of 100 ul, but only 50 ul is needed for the lab; thus, 50 ul will normally be discarded
If assay is ~50 ul or less, then the sample can be split at the machine, blood can be picked up by the study coordinator, processed, and saved

29. What We Are Learning Initially
Most academicians hated the idea
Many clinical pharmacologists were skeptical but open-minded
Bedside clinicians loved it
Product stability, product half-life, and assay technical components are key
Accuracy of sample collection time
How long it sits in the lab
Only so much blood and multiple types of tubes
Motivated investigators (some none, some per patient)
Need traditional sampling linked to scavenge within trial and for most enrollees, within each patient
Longer “window” to collect works well with motivated investigators
Fluconazole for 6 weeks
Meropenem multiple doses
Single-dose study
For commonly used drugs (metronidazole), provide preliminary data to help design a traditional PK study (or PK-safety study). Data can later be combined with more data from more traditional designs

30. Example Study Protocol: Pediatric Opportunistic PK Study
Protocol Chair: Cohen-Wolkowiez (Duke)
Protocol: Pharmacokinetics of Understudied Drugs Administered to Children per Standard of Care (POPS)
Total number of drugs studied = 11
Objectives: Evaluate the PK of understudied drugs currently being administered to children
Study Population: ~1000 children (birth-20 years)
Study Duration: Up to 90 days per drug
Number of Sites: ~35
November 2011, First patient enrolled
First publication: Determining Population and Developmental Pharmacokinetics of Metronidazole Using Plasma and Dried Blood Spot Samples From Premature Infants Pediatric Infectious Diseases Journal April 12, 2013

31. Background In preterm infants, intra-abdominal infections are deadly
These infections are polymicrobial, including anaerobes
Metronidazole has excellent anti-anaerobic activity
Pharmacokinetic data of metronidazole in preterm infants are limited
Blood volume is a limiting factor for studies in neonates
Dried blood spots require 10 times less blood per sample vs. plasma

32. Methods Multicenter (N=3), open-label, PK study N=24 Population
Gestational age at birth <32 weeks
Postnatal age (PNA) <91 days
Suspected serious infection
Dosing (intravenous)
Loading dose 15 mg/kg
Maintenance dose 7.5 mg/kg every hours for 5 days

33. Methods
Sampling
Paired plasma and dried blood spots collected if possible
Last dose, PNA < 14 days
hours
hours
Last dose, PNA ≥ 14 days
Dose 1, & 3-5
hours
Population PK
Nonlinear mixed effects modeling using NONMEM software and bootstrapping to evaluate precision of parameters
Plasma and dried blood spot samples analyzed separately
Plasma and dried blood spot paired concentrations analyzed by linear regression

34. Subject Demographics

35. Population Pharmacokinetic Parameters

36. Dried Blood Spot Correlation
r2=0.95, slope=0.80 [95% CI, 0.74, 0.85], p<0.001
r2=0.85, p<0.001
N=46 paired samples

37. Conclusions Acknowledgments
Metronidazole clearance increased with postnatal age
Clearance finding expected with development
The bias in population clearance and volume parameter estimates was <10% using dried blood spots
DBS sampling can be used to evaluate metronidazole pharmacokinetics
Acknowledgments
Pediatric Trials Network
Data Coordinating Center
Daniel Benjamin Jr.
EMMES Corporation
Edmund Capparelli
NIGMS/NICHD UNC-Duke Collaborative T32 Clinical Pharmacology Postdoctoral Training Grant, National Institutes of Health (1 T32 GM 86330)
Gregory Kearns
Philip Brian Smith
Michael Cohen-Wolkowiez
Kim Brouwer
Katherine Berezny
Barrie Harper
Paul Watkins
Enrolling Sites
Eunice Kennedy Shriver National Institute of Child Health and Human Development (NIH)
Children’s Hospital of Orange County
- Antonio Arrieta
Contract #: HHSN and HHSN I
Duke University Medical Center
- James Wynn
Task Order #: HHSN
Wesley Medical Center
Best Pharmaceuticals for Children Act
- Barry Bloom
University of North Carolina Eshelman School of Pharmacy
- Paula Delmore

38. Interpretation for Drugs

39. Key Parameters for Interpretation
Method of Dosing
Oral Pill
Sublingual
Topical
Injection (fast release)
Injection/Implant (slow release)
Plasma Binding
Distribution between cells and plasma
Clearance pathway
Random vs Trough sampling

40. Antiepileptic Drugs
Camilla Linder, Katarina Wide, Malin Walander, Olof Beck, Lars L Gustafsson, Anton Pohanka, Comparison between dried blood spot and plasma sampling for therapeutic drug monitoring of antiepileptic drugs in children with epilepsy: A step towards home sampling, Clinical Biochemistry 50 (2017) 418–424
Fig. 1. Scatter plots with Passing and Bablok fit. Correlations of plasma measured with routine method and DBS measured with an LC-MS/MS method for lamotrigine, carbamazepine and valproic acid. Dotted lines are identity lines, continuous lines representing Passing & Bablok regression. R2 values from simple linear regression and Passing & Bablok equation for carbamazepine: R2 = (n = 17) y = 1.32x − 0.44 with a 95% CI for slope: 1.01 to 1.45,intercept: −1.29 to 0.78, lamotrigine: R2 = (n = 20) y = 1.18x − 0.39 with a 95% CI for slope: 0.32 to 1.32, intercept: −1.01 to 0.96 for valproic acid R2 = (n = 33) y = 0.67x − with a 95% CI for slope: 0.58 to 0.76, intercept: −7.70 to 4.16.

41. Gabapentin
Nele Sadones, Elien Van Bever, Luc Van Bortel, Willy E. Lambert, Christophe P. Stove, Dried blood spot analysis of gabapentin as a valid alternative for serum: a bridging study, Journal of Pharmaceutical and Biomedical Analysis, Volume 132, 2017, 72–76
Fig. 2. Passing-Bablok regression analysis plotting the serum concentrations calculated from the blood concentrations against the measured serum concentrations. The slope and intercept of the regression line (solid line) are calculated with their 95% confidence
Fig. 1. Passing-Bablok regression analysis plotting the DBS concentrations against the serum concentrations. The slope and intercept of the regression line (solid line) are calculated with their 95% confidence interval (dashed line). The dotted line correspond...

42. Comparison of Toxicology Assays from Urine and Dried Blood Specimens
Feature
Urine
DBS
POC screen available 
Laboratory screen available
Drug concentration can be quantified
Comprehensive list of drugs
Typical detection window (days)
7-21
5-14
Easy to collect
Can be collected by anyone
Can be collected from all patients
Protects patient privacy
No risk of adulteration
Can be collected at home and mailed in
Stable at room temperature for weeks
Can be sent through the mail without special packaging
Compensates for genetic heterogeneity
Independent from kidney function
Definitive, actionable therapeutic range

43. Comparison of Detection Window from Oral Fluid and DBS
Drug
Analyte Detected
DBS LLOQ (ng/mL)
Oral
DBS
min (hr)
max (hr)
min (day)
max (day)
carbamazepine
200 24 48 5 7
imipramine 10 3
Gabapentin
250 2 4
Ketamine 1
haloperidol
Levorphanol
lamotrigine 9
Lorazepam 20 12
levetiracetam
500
LSD
Lysergic Acid Diethylamide
Methadone
Methadone trough
MDPV
Methadone peak 6
Meperidine
oxcarbazepine
10-monohydroxyoxcarbazepine
Mephedrone
topiramate
Meprobamate
valproic acid
5000
Methamphetamine
MDA
Alprazolam
MDMA
Amitriptyline
Methylone(MDMC)
Amphetamine
Methylphenidate
Aripiprazole 8 16
Mirtazapine
Buprenorphine
0.5
Morphine
Norbuprenorphine
Naloxone
bupropion
Naltrexone
Butalbital 72
6-B_Naltrexol
Carisoprodol
nortriptyline
Citalopram, Escitalopram
Citalopram (racemate)/ Escitalopram (S-citalopram)
olanzapine
Clonazepam
Oxazepam
clozapine
Oxycodone
Noroxycodone
desmethylclozapine
Cocaine
Benzoylecgonine (BZE)
Oxymorphone
Codeine
paroxetine
Norcodeine
Pentazocine
Cotinine
120
Phencyclidine (PCP)
Cyclobenzaprine
Phenobarbital 18
desipramine
Phentermine
desvenlafaxine
O-Desmethylvenlafaxine
pregabalin
100
Dextromethorphan
quetiapine
Diazepam 14
risperidone
nordiazepam
9-Hydroxyrisperidone (paliperidone)
doxepin
sertraline
Duloxetine
Tapentadol
eszopiclone
Zopiclone (racemic) or eszopiclone
Temazepam
Ethanol
phosphatidylethanol 45
THC
THCA (THC-9 carboxy)
Fentanyl
Tramadol
Norfentanyl
trazodone
fluoxetine
venlafaxine
norfluoxetine 40 90
O-desmethylvenlafaxine
Heroin
Monoacetylmorphine (6-MAM)
zaleplon
Hydrocodone
ziprasidone
Hydromorphone
Zolpidem

44. Interpretation for Steroids

45. Key Parameters for Interpretation
Method of Dosing
Oral Pill
Sublingual
Topical
Injection (fast release)
Injection/Implant (slow release)
Plasma Binding
Circulating vs Sequestered
Clearance pathway

46. Steroids – DBS vs Immunoassay
Figure 2. Relationship between 17-OHP concentrations measured by immunoassay and LC–MS/MS in DBS of children participating in
the Dutch Neonatal Screening Program, distinguished on GA.
GA: Gestational age.
Anita Boelen*, An FC Ruiter, Hedi L Claahsen-vander Grinten, Erik Endert, Mariette T Ackermans, Determination of a steroid profile in heel prick blood using LC–MS/MS, Bioanalysis (2016) 8(5), 375–384

47. Steroids – DBS Screening
Figure 3. Steroid profile in DBS of children with a positive congenital adrenal hyperplasia screening (n = 92, 17-OHP-NS above cut-off
value), concentrations are given in nmol/l. Square symbol represents a DBS from a child diagnosed with CAH, star symbol represents a DBS from a child with late onset CAH.
11-DF: 11-deoxycortisol; 11-DOC: 11-deoxycorticosterone; 17-OHP:17-hydroxyprogesteron; 21-DF: 21-deoxycortisol; A4: Δ4-androstenedion; B: Corticosterone; CAH: Congenital adrenal hyperplasia; E: Cortisone; F: Cortisol.
Anita Boelen*, An FC Ruiter, Hedi L Claahsen-vander Grinten, Erik Endert, Mariette T Ackermans, Determination of a steroid profile in heel prick blood using LC–MS/MS, Bioanalysis (2016) 8(5), 375–384

48. Interpretation for Chemistries

49. Key Parameters for Interpretation
Location of Analyte in Blood
Most Traditional assays are on Plasma/Serum
Impact of Hemolysis on Measurement
Impact of dried sample for DBS
Cell counting
Coagulation cascade
Enzyme activity
Free vs Bound

50. Reference Ranges – DBS

51. Conclusions

52. Conclusions
Microsampling is a proven methodology with evolving improvements in application
Technology has advanced to enable microsampling for many common applications
Microsampling has advantages for
Patient experience
Ease of collection
More meaningful data in certain circumstances
Interpretation requires assessment of matrix differences