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DIGITAL BIOMARKERS DIGITAL BIOMARKERS

VIUM.COM | [email protected] | +1 (650) 797-2000

Vium.com | +1 (650) 797-2000 | [email protected]

Breathing Rate ChangesMonitored Non-Invasively 24/7

INTRODUCTION

VIUM BREATHING RATE

BIOMARKER VALIDATION

Breathing Rate

Measuring changes in Breathing Rate can lead to the early detection of disease (1) and is key in evaluating

the safety profile of novel therapeutics (2), (3). A range of conditions including exercise, stress, lung disorders,

cardiovascular disease, metabolic acidosis, drug overdose, and central nervous system abnormalities can all

manifest in detectable alterations in Breathing Rate (1), (3-5).

Vium Breathing Rate (breaths per minute) is derived from continuous

video streams of animals in Vium Smart Housing. Computer vision

algorithms search for regions of time when animals are stationary, and

identify periodic motion that falls within a frequency band containing

known rodent breathing rates (6). The peak root mean square (RMS)

power is compared to a threshold to determine whether the periodic

motion is significant.

Vium Breathing Rate was compared to breathing rate measured by

conventional whole-body plethysmography of awake mice with

known differences in baseline breathing rate (3).

• Compare baseline and post-therapeutic intervention breathing rates

• Evaluate drug efficacy in models that use breathing rate as a readout

• Obtain an early indication of off-target effects and/or potential safety signals

• Track breathing rate over time to assess disease progression and acute conditions

Preclinical Researchers Use This Biomarker to:

METHODSSix-week old male C57BL/6J and C3H/HeJ mice were acclimated to

Vium Smart Housing for a total of one week prior to commencing the

study. Animals were singly housed three days prior to study start.

Unrestrained animals were placed in a whole-body plethysmograph

(EMKA technologies), and breathing rate was simultaneously collected

via plethysmograph and the Vium Breathing Rate algorithm.


RESULTS

Our Breathing Rate Biomarker was compared to breathing rate measured by the plethysmograph (Fig. 2, R2 = 0.981; RMS error = 3.7%). In this validation, we demonstrated that Vium Breathing Rate has a 95% confidence interval of -2.9% to +8% of the breathing rate observed by plethysmograph. Consistent with the literature6 we observed that C3H/HeJ mice had a significantly lower breathing rate (136.3 +/- 3.2) than C57BL/6J animals (180.7 +/- 3.7) [ANOVA: F(1,27) = 65.99; p < 0.0001].

DISCUSSION

We have successfully demonstrated that Vium Breathing Rate accurately measures breathing rate. The Vium Digital Vivarium Platform provides an unprecedented opportunity to obtain continuous real, in cage, breathing rate data, over the course of a study, without the need for human intervention. Removing the human intervention eliminates the introduction of variables associated with stress and anxiety, known to affect animal physiology. This results in more reliable and reproducible data from which scientists can glean valuable information on drug safety and efficacy and provides data not often assessed due to the laborious and notoriously unreliable conventional methods of collection.

REFERENCES1. Braun SR. Respiratory Rate and Pattern. In: Walker HK, Hall WD, Hurst JW, editors. ClinicalMethods: The History, Physical, and Laboratory Examinations. 3rd edition. Boston: Butterworths;1990. Chapter 43. 2. Pugsley MK, Authier S, Curtis MJ. Principles of safety pharmacology. Br J Pharmacol. 2008Aug;154(7):1382-99. 3. Murphy DJ. Assessment of respiratory function in safety pharmacology. Fundam Clin Pharmacol.2002 Jun;16(3):183-96.4. Dick TE, Hsieh YH, Dhingra RR, Baekey DM, Galán RF, Wehrwein E, Morris KF. Cardiorespiratorycoupling: common rhythms in cardiac, sympathetic, and respiratory activities. Prog Brain Res.2014;209:191-2055. Jerath R, Barnes VA, Crawford MW. Mind-body response and neurophysiological changes duringstress and meditation: central role of homeostasis. J Biol Regul Homeost Agents. 2014 OctDec;28(4):545-54. 6. Groeben H, Meier S, Tankersley CG, Mitzner W, Brown RH. Heritable differences in respiratorydrive and breathing pattern in mice during anaesthesia and emergence. Br J Anaesth. 2003Oct;91(4):541


Continuously Monitor Motion In Real Time

Motion Biomarker

INTRODUCTION

Observation and quantification of freely moving animals is a powerful tool for understanding the effects of genetic, environmental, and therapeutic manipulations on physiology and behavior (1,2). Numerous studies have demonstrated that animal strain, environment, handling, pharmacological agents, disease conditions, aging, stress, and altered neurological states can impact quantifiable aspects of animal activity (2-7). Measurement of overall activity, as well as specific subtypes of activity such as circadian rhythms and particular aspects of locomotion, can be used as an integrated readout for tracking disease progression.

• Continuously monitor animal

activity in near-real time

• Conduct short-term studies to

track acute effects of therapeutic

interventions

• Conduct long-term studies to

monitor delayed and/or chronic

treatment effects

• Document the natural history of

animal disease models


VIUM MOTION BIOMARKER

BIOMARKER VALIDATION

Vium’s automated sensors and computer-vision algorithms provide continuous observation using HD video captured at 24 frames per second (Figure 1). Our proprietary algorithms discriminate and quantify animal behaviors including spontaneous wheel-running, breathing rate, and circadian activity.

Our platform’s ability to accurately measure motion across a range of at speeds up to 5 cm/s was validated using a speed-controlled visual target placed within Vium Smart Housing.

METHODS AND RESULTSA visual target, placed within a standard Vium Smart House, was set to move at physiologically relevant speeds ranging from 5 – 50 cm/s. Raw video was transformed into cage-floor coordinates, and rendered into velocity measurements via computer vision analysis (8). The speed estimated using computer vision video analysis was compared to actual speed of the visual target in both high density (mouse size) and low density (rat or mouse) Smart Houses (Fig. 2). Confidence interval is based on mean and standard deviation of the percentage error.


DISCUSSION

Our validated Motion Biomarker is used to detect changes in overall animal activity, and also to derive

biomarkers to assess disease progression in a variety of rodent models, such as Rheumatoid Arthritis,

potentially replacing the need for more laborious and less reliable conventional measurements. Detection of

these features of animal activity could be used as direct readouts of therapeutic efficacy in relevant models, as

a source of insights into novel or unexpected drug effects, as an indicator of animal health or moribund status,

and/or as an early indication of potential safety signals.

REFERENCES1. Irwin S. Comprehensive observational assessment: Ia. A systematic, quantitative procedure for assessing

the behavioral and physiologic state of the mouse. Psychopharmacologia. 1968 Sep 20;13(3):222-57.

2. Crawley JN. Behavioral phenotyping strategies for mutant mice. Neuron. 2008 Mar 27;57(6):809-18

3. Crabbe JC, Wahlsten D, Dudek BC. Genetics of mouse behavior: interactions with laboratory

environment. Science. 1999 Jun 4;284(5420):1670-2.

4. Chesler EJ, Wilson SG, Lariviere WR, Rodriguez-Zas SL, Mogil JS. Influences of laboratory

environment on behavior. Nat Neurosci. 2002 Nov;5(11):1101-2.

5. Chesler EJ, Wilson SG, Lariviere WR, Rodriguez-Zas SL, Mogil JS. Identification and ranking of

genetic and laboratory environment factors influencing a behavioral trait, thermal nociception, via

computational analysis of a large data archive. Neurosci Biobehav Rev. 2002 Dec;26(8):907-23.

6. Wahlsten D, Bachmanov A, Finn DA, Crabbe JC. Stability of inbred mouse strain differences in

behavior and brain size between laboratories and across decades. Proc Natl Acad Sci U S A. 2006

Oct 31;103(44):16364-9.

7. Gallagher M, Rapp PR. The use of animal models to study the effects of aging on cognition. Annu

Rev Psychol. 1997;48:339-70.


Continuously Monitor Animal Wheel Running Activity

Running Wheel

INTRODUCTIONThe Vium Digital Vivarium Platform offers two different types of activity biomarkers, which allow researchers to dissociate overall physical activity and voluntary activity: Vium Motion and Vium Percentage (%) Time Running on Wheel. Vium Motion measures overall activity, which is comprised of both voluntary and involuntary motor movements, including wheel running, as well as a wide range of complex behaviors, such as eating drinking and grooming. These behaviors contribute to background activity levels, especially during the light cycle when animals are less active. In contrast, Vium % Time Running on Wheel specifically captures free running on the wheel, which accounts for voluntary activity. A number of factors are known to differentially alter overall physical activity and voluntary wheel running activity (1,2).

• Continuously and automatically monitor percentage time animal spent running on wheel with both low and high resolution time bins

• Complement overall and spontaneous physical activity (Vium Motion Biomarker)

• Measure short- and long-term changes in animal behavior, physiology, and well-being

• Assess circadian rhythm patterns

• Evaluate therapeutic interventions in animal models of disease


Running wheels are commonly employed in rodent research not only to provide animal enrichment, but to measure physical activity and circadian rhythm pattens (1). Wheel running provides valuable information on many aspects of an animal’s well-being and physiology, including motor function, energy balance, cognition, as well as stress-, anxiety, and depression-like behaviors (2,3). Wheel running activity has also been reliably used as a gold standard for measuring circadian rhythm patterns, therefore becoming an invaluable tool for phenotyping and investigating a number of disease models, including aging, metabolic, psychiatric, and neurological diseases (4-6).

PERCENTAGE TIME RUNNING ON WHEELThis determines whether a mouse is running on the wheel on a frame-by-frame basis and reports the percentage (%) of time spent running on the wheel. To derive this biomarker, computer vision algorithms locate animals in the wheel zone of the home cage and determine if they are running on the wheel (Fig. 1). The result is reported as a binary output: 1 for animal running on the wheel and 0 for animal not running on the wheel. These outputs are then aggregated into time bins (ex. 60-sec, 600-sec, or 3600-sec bins),

Figure 1. Schematic depicting generation of percentage (%) time running on wheel. Computer vision algorithms locate running wheel zone then detect binary event (1=mouse is running on wheel for full 1-sec video clip, 0=mouse is not running on the wheel for full 1-sec video clip). Events are aggregated into time bins and can be visualized for individual subjects or as group averages in the online Research Suite.

wherein each bin represents the percentage time the animal spent running on the wheel (total number of instances running / total number of frames * 100).


DISCUSSION

Here we show that Vium Percentage (%) Time Running on Wheel provides automated, continuous, and accurate determination whether an animal is running on the wheel. Depending on the goals of the experiment, low and high-resolution time bins can be investigated for individual subjects or as group averages on the online Research Suite.

We also demonstrate the capability of this digital biomarker to investigate mouse models of disease. In a cuprizone mouse model of Multiple Sclerosis (MS), a representative subject showed periods of attenuated wheel running activity, which may indicate periods of decreased gross motor function resulting from demyelination (7). In conjunction with spontaneous physical activity, wheel running can be used not only to detect changes in overall activity, energy homeostasis, cognition, and social behaviors, but also to acquire more sensitive measurements of circadian rhythm patterns over short and long-term periods of time (2-5). Vium % Time Running on Wheel can be used as a direct readout for the evaluation of compound therapeutic efficacy and investigation of animal models of aging and disease (5,6).

REFERENCES1. Hendershott TR, Cronin ME, Langella S, McGuinness PS, Basu AC. Effects of environmental enrichment on axiety-like behavior, sociability, sensory gating, and spatial learning in male and female C57BL/6J mice. Behav Brain Res. 2016; 314:215-225.2. Novak CM, Burghardt PR, Levine JA. The use of running wheel to measure activity in rodents: relationship to energy balance, general activity, and reward. Neurosci Biobehav Rev. 2012; 36(3):100-1014. 3. Morgan JA, Singhal G, Corrigan F, Jaehne EJ, Jawahar MC, Baune BT. The effects of aerobic exercise on depression-like, anxiety-like, and cognition-like behaviours over the health adult lifespan of C57BL/6 mice. Behav Brain Res. 2017; pii:S0166-4328(17)31012-4. 4. Jud C, Schmutz I, Hampp G, Oster H, Albrecht U. A guideline for analyzing circadian wheel-running behavior in rodents under different lighting conditions. Biol Proced Online. 2005; 7:101-116. 5. Valentinuzzi VS, Scarborough K, Takahashi JS, Turek FW. Effects of aging on the circardian rhythm of wheel running activity in C57BL/6 mice. Am J Physiol. 1997; 273(6 Pt 2):R1957-1964. 6. Mandilo S, Heise I, Garbugino L, Tocchini-Valentini GP, Giuliani A, Wells S, Nolan PM. Early motor deficits in mouse disease models are reliably uncovered using an automated home-cage-wheel-running system: a cross laboratory validation. Dis Model Mech. 2014; 7(3):397-407. 7. Liebetanz D and Merkler D. Effects of commissural de- and remyelination on motor skill behavior in the cuprizone mouse model of multiple sclerosis. Exp Neurol. 2006; 202(1):217-224.


Automated Index to Track Disease Progression

Vium Arthritis Index

INTRODUCTIONAnimal models of arthritis are routinely used to evaluate the efficacy of therapeutics for Rheumatoid

Arthritis (RA). A variety of pharmacologically induced and transgenic animal models have been developed,

each capturing a different facet of human pathophysiology (1-3). As a result, researchers must select the

model that is best suited to the disease mechanisms targeted by their therapeutic candidates. Metaanalysis of

animal studies has revealed that drugs displaying therapeutic efficacy in both Collagen Induced Arthritis (CIA)

and Adjuvant Induced Arthritis (AIA) models are most successful in the clinic (1).

The Vium Arthritis Index™ enables researchers to evaluate the

efficacy and safety of therapeutic interventions in rodent models of

RA through near realtime measurements and data analysis. Our

use of physiological measurements combined with advanced

analytics provides a highly sensitive readout of arthritis induction,

as well as clinically relevant measures of therapeutic response.

The net result is that researchers can non-invasively assess

treatment effects during the course of the study, and make on-

the-fly decisions about which treatment arms are worth

continuing.

VIUM ARTHRITIS INDEX

• Improve Flexibility: Use standard rat CIA or AIA models or customize study designs.

• Collect data in the home cage non-invasively and reduce extraneous variables and labor involved in animal handling and observation.

• Conduct adaptive preclinical studies using digital endpoints that closely track with conventional methods.

• Automated sensors are on 24/7, giving researchers access to additional general health biomarkers.


BIOMARKER VALIDATIONWe have conducted a series of experiments demonstrating 1) that

we are able to induce arthritis using standard models such as rat CIA

and 2) that the Vium Arthritis Index accurately tracks disease severity

and prophylactic treatment efficacy when compared to conventional

measurements.

METHODSThe rat CIA model was conducted according to standard protocols

(4,5). Briefly, Lewis rats were inoculated with Porcine collagen type

II (2 mg/mL) in Incomplete Freund’s Adjuvant (IFA). Control animals

were induced with IFA only. On study day 0, rats were given 200 μl

intradermal injections on the back at 2 sites, and a single 100 μl

booster injection was given on day 7. Test compound

administration began on day 9 and continued according to the

following dosing regimens:

• Vehicle (daily)

• Methotrexate (MTX, 0.075 mg/kg, daily PO)

• Ibuprofen (18 mg/kg, daily, PO)

• Enbrel (10 mg/kg q3d SC)

• Dexamethasone (DEX, 0.075 mg/kg, daily PO)

The Vium Arthritis Index and daily joint size measurements were

made for the duration of the study, with organ weight (spleen, liver)

and ankle joint histopathology determined after study termination.


RESULTSArthritis developed in collagen-induced animals within

the expected time window of 11 – 13 days as measured

either by joint size or the Vium Arthritis Index (Fig. 1). The

Vium Arthritis Index tracked with joint size measurements

for each of the drugs tested (Fig. 2). Furthermore, the data

mirrored the rank ordering of the three standard of care

drugs as determined by ankle joint histopathology,

indicating that the Vium Digital Platform can be used to

determine the relative efficacy of test articles. In a follow-

on study, we tested 9 compounds at 3 doses each in the

CIA model. Using the Vium Arthritis Index, we ranked the

compounds by therapeutic efficacy to rapidly identify

high performing compounds.

REFERENCES1. Hegen M, Keith JC Jr, Collins M, Nickerson-Nutter

CL. (2008) Utility of animal models for identification

of potential thereapeutics for rheumatoid arthritis.

Ann Rheum Dis. 67: 1505-15.

2. Bevaart L, Vervoordeldonk MJ, Tak PP. (2010)

Evaluation of therapeutic targets in animal models

of arthritis: how does it relate to rheumatoid

arthritis? Arthritis Rheum. 62: 2192-205.

3. Bendele A. (2001) Animal models of rheumatoid

arthritis. J Muscoloskelet Neuronal Interact. 1: 377-85.

4. Trentham DE, Townes AS, Kang AH. (1977)

Autoimmunity to type II collagen an experimental

model of arthritis. J Exp Med. 146: 857-68.

5. Courtenay JS, Dallman MJ, Dayan AD, Martin A,

Mosedale B. (1980) Immunisation against

heterologous type II collagen induces arthritis in

mice. Nature 283: 666-8.

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