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TD Glucose TM Monitoring System Technical Review.

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Presentation on theme: "TD Glucose TM Monitoring System Technical Review."— Presentation transcript:

1 TD Glucose TM Monitoring System Technical Review

2 Overview 1.Brief introduction to Health-Chems R&D Philosophy Product oriented approach 2.Show videos 3.Update on current clinical results Show representative clinical examples 4.Review general & basic understanding Transdermal Drug Delivery (TDD) 5.Relate basic TDD facts TD Glucose Monitoring System (TD-G) information Hypothesize on underlying product mechanisms 6.Q & A

3 R&D PHILOSOPHY 100% Product-Oriented R&D focus –NO academic research to prove and investigate theoretical concepts –All R&D efforts are focused solely on product development –Assure that product works and introduce into market fast –After product introduction, theoretical concepts will be investigated and researched by academia or other organizations –Health-Chem supports these efforts, but will not take on a leading role

4 ASSURE PRODUCT FUNCTIONALITY Mainly Lab Work … –Produce product and demonstrate that it achieves desired goal and objective Generate all pertinent information required for FDA approval … supported by Theoretical Review Assure that theoretical mechanisms and available scientific background information can explain or support the feasibility of the new product

5 VIDEOS BBC - Weekly Science and Technology Program - -Tomorrows World (6/2/99) 1 1 CBS Ch4 - St. Louis Station KMOV-TV - -On local News Segment (8/5/99) 2 2 CBS - Nationwide The Early Show - -HealthWatch Segment (11/17/99) 33

6 UPDATE – CLINICAL DATA WashU Study Objective -Confirm patch performance in hypo & hyperglycemic range Triggered by Barcelona, Spain, Presentation 9/98 (Dr.s Office) Basic Study Design -Enrolled 13 patients (3 Type I & 10 Type II) Hospitalized, under constant medical supervision Infusion lines for glucose and insulin delivery Catheter for venous blood sampling Glucose Measurements 1.Venous blood glucose was analyzed w/ YSI ==> mg/dL 2.Capillary blood w/Fingerstick (OneTouch) ==> mg/dL 3.TD-G patch ==> mV Develop correlation model, evaluate best fit parameters

7 MATHEMATICAL CORRELATION Fit TDG Data to corresponding REFERENCE data Fit TDG Data to corresponding REFERENCE data –Simple 2-parameter Model: TDG = (INT - mV)*MPL TDG = (INT - mV)*MPL –Choose correlation model parameters (INT & MPL) GOAL: Correlation curve on centerline in Clarke ERROR Grid Slope = 1, Intercept = 0 Evaluate feasibility of UNIVERSAL Correlation Evaluate feasibility of UNIVERSAL Correlation

8 PATCH METER SYSTEM Patch Proprietary detection membrane All patch materials -can be easily mass produced -very cost efficient -GMP -track record with FDA (cosmetic or medical use) Patch assembly still manual Meter Dual optics Operator Error correcting software not implemented, yet!

9 PATIENT GF-WU4R Glucose Profile (YSI, Fingerstick & Patch) Glucose Profile (YSI, Fingerstick & Patch) Model Parameters: 810 - 3.4

10 PATIENT RF-WU5 Glucose Profile (YSI, Fingerstick & Patch) Glucose Profile (YSI, Fingerstick & Patch) Model Parameters: 798 - 4.8

11 PATIENT CM-WU9 Glucose Profile (YSI, Fingerstick & Patch) Glucose Profile (YSI, Fingerstick & Patch) Model Parameters: 796 - 5.3

12 PATIENT RL-WU14 Glucose Profile (YSI, Fingerstick & Patch) Glucose Profile (YSI, Fingerstick & Patch) Model Parameters: 809 - 4.8

13 SUMMARY – INDIVIDUAL Each patient individually fitted y = 1.00x + 0.27 R 2 = 0.93 0 50 100 150 200 250 300 350 400 450 500 550 600 0100200300400500600 Reference Blood Glucose - YSI (mg/dL) TDG (mg/dL) E E D D A A B B C C WU4 - 16 outliers

14 MODEL PARAMETER ANALYSIS Found excellent prediction/correlation Found excellent prediction/correlation Both parameters vary from patient-to-patient Both parameters vary from patient-to-patient –INT parameter varies less then MPL parameter; <1% compared to 17% Reasons for variations? Reasons for variations? –Variety of causes electronics related issues electronics related issues physiological differences (skin) physiological differences (skin) else! else! Overall, small fluctuation Overall, small fluctuation –Universal Calibration? INTMPL Wu4812 3.3 Wu57984.8 Wu67895.2 Wu77935 Wu8 8024.4 Wu97965.3 Wu10808 5 Wu117935.6 Wu127985 Wu13 7946.7 Wu14809 4.8 Wu15809 5.4 Wu168026.7 8005.2 70.9 0.9%17.1%

15 Summary – UNIVERSAL y = 1.01x - 0.52 R 2 = 0.84 0 50 100 150 200 250 300 350 400 450 500 550 600 0100200300400500600 Reference Blood Glucose - YSI (mg/dL) TDG (mg/dL) E E DD A A B B C C WU4 - 16 Universal Parameters: 800/5.2 Every patient fitted with AVG Model parameters

16 DISCUSSION Scatter probably related to non-optimized product – Worst case scenario – Hand-made patches compared to fully automated MFG – Meter software not fully implemented (correction algorithms) slide slide Individual calibration resulted in excellent correlation between TDG and YSI or Fingerstick – NEXT STEP: Compare to Cygnus UNIVERSAL calibration? – Acceptable for FDA approval? Likely, need more data!

17 CONCLUSION – CLINICAL DATA TD Glucose System is successful in predicting hypo & hyperglycemic range Accuracy of prediction is similar to YSI and Fingerstick Recent data suggest that UNIVERSAL patient calibration may be achievable

18 THEORY SECTION Where is the Glucose - collected in the patch - coming from?

19 ASSUMPTION TD-G based on dermal or transdermal mechanisms

20 THEORETICAL CONCEPT Glucose partitions into / exchanges between compartments – Blood, ISF & Skin Tissues

21 GLUCOSE AND SKIN Non-invasive blood glucose monitoring systems under development using skin as portal Electro transport Infrared technique Light absorption reverse transdermal Conventional Health-Chem Rationale: Prevent lancing the skin to draw blood Inconvenient and distressful (daily basis, several times a day) Allow for more frequent daily monitoring

22 GLUCOSE AND SKIN (contd) TD-G based on the facts that: -Glucose levels equilibrate between blood and interstitial fluids (Lonnroth et. al., Am. J. of Physiology, 253: E228-31, 1987) -Skin glucose varies in synchrony with blood glucose levels during tolerance testing (Fusaro et. al., J. Invest. Dermatol., 42: 359, 1964) -Skin tissue when immersed into glucose solutions equilibrates linearly with external glucose concentration (Halprin et. al., J. Invest. Dermatol., 49(6): 561, 1967) Available information supports concept of a dermal or transdermal type mechanism

23 Transdermal Drug Delivery Typically focus on enhancer formulations to facilitate -partitioning into and diffusion through skin layer (Ficks Law) -in particular SC and epidermis

24 Schematic Transport Routes & Equations TD-G Patch Gel SCISF/(Epi)DermisBlood JPJP JDJD Total Transport = Sum of transports through dense and porous sections Total Transport = Sum of transports through dense and porous sections DENSE membrane: J D = P D · c D POROUS membrane: J P = P P · c P + c·(1- ) J v [ J v = L p ( p- g ) ] Compartments Glucoseexchanges between betweencompartments

25 Porous Membrane Concept J P = P P · c P + c·(1- ) J v J P = P P · c P J P = c·L p p (at steady state) Permeability P P is proportional to number of pores to number of pores Permeability L P is proportional to porosity, tortuosity, etc. to porosity, tortuosity, etc. SUCTION J P,c J P,d Patch Reservoir SCISF/(Epi)DermisBlood

26 SKIN HYDRATION Sweating may have impact on glucose transport to the skin surface -Pores, sweat ducts, hair follicle shafts, etc. -Transcellular route (swollen keratinocytes) -Intracellular route via water section of the lipid bilayer Clinical data supports this thinking -Patients under hypoglycemic stress experience profuse sweating -Measurements at this extreme condition typically show stronger meter responses suggesting more glucose was transported to skin surface via transpiration -Needs continued research to develop appropriate counter measures

27 Dense Membrane Concept (J P = 0) Skin Area with NO Pores diffusive J D = P D · c D Permeability P D can be modified by skin permeation enhancers Ficks Law (Steady State) JDJD

28 WHAT IS THE ACTUAL TRANSPORT PROCESS? At the time not absolutely defined Safe to speculate that glucose partitions into the adjoining tissues How it gets there is with high probability a mix of -Regular intracellular and extra-cellular diffusive transport -Shunt transport through Hair follicles Sweat ducts -Other? Hydration, ionic convection (see Cygnus), etc. References for glucose skin flux

29 GLUCOSE SKIN FLUX Examples: US#5,139,023 > 4 g/cm 2 min flux = f(c) Cygnus * 6 ng/cm 2 min * Private conversation

30 THEORETICAL ESTIMATION Melting Point Theory Baker, R., Kochinke, F., 1988. "Transdermal Drug Delivery Systems", Controlled Release of Drugs: Polymers and Aggregate Systems. VCH, 277-305 m p 150°C 0.1 g/cm 2 hr 2 ng/cm 2 min

31 CONCLUSION / ANSWER Glucose collected in the patch originates from skin We dont know the exact pathways and related transport parameters Glucose travels along regular transdermal routes Experimentally and theoretically determined glucose skin flux values are very different Qualitatively, data suggest glucose is crossing the skin Quantitatively?

32 ADD DATA TO THEORY What and How Much is the Patch measuring?

33 QUALITY CONTROL TESTING Patches are charged with defined glucose quantities 40 l gel with increasing finite amounts of glucose 3 patches per STD STD span the complete range of in vivo elicited responses y = -0.2705x + 789.26 R 2 = 0.9962 550 650 750 850 0100200300400500 Standards (ng/40 l) Meter Reading (mV) 1 2 3 Patch Average (STD = 0.8%) linear (Patch Average) INT (?)? In Vivo finite Glucose amount from Skin

34 CALCULATED GLUCOSE FLUX STD Calibration Testing (less than 5 minutes): 20 to 300 ng per 0.5 cm 2 40 to 600 ng/cm 2 Corresponding flux value ~ 8 – 120 ng/cm 2 min Hypothesis: Membrane response can be elicited by 1. a STEADY glucose skin flux or 2. the glucose already partitioned into and available to the patch from the outermost skin layers

35 STEADY FLUX ? Membrane reaction has an Endpoint Endpoint suggests a limited or finite amount of glucose is detected by the membrane Reaction is concentration-dependent STEADY Skin Flux would NOT allow Endpoint Constant supply of glucose, reaction would continue In addition, lag time does not allow STEADY flux in the initial time interval

36 LAG TIME Certain time for the steady state flux to develop: Lag TimeTime interval to establish steady state flux Before SS Flux reached immediateleachable amount Cant measure reliably (poor assay sensitivity) Health-Chem membrane can! Within 3 minutes: 0.34 g through 1.89 cm 2 180 ng/cm 2 Comparable amount to Health-Chem findings compare compare Steady State Flux Region Immediately Leachable Amount

37 PARTITIONING Glucose equilibrates between compartments Leachable amount increases with rising blood level Activit y c/c s Concentration Steady State SC ISF/Dermis Blood SC ISF/Dermis Blood

38 REVERSE TRANSDERMAL MECHANISMS Conventional Measure in steady state region e.g. Cygnus Health-Chem Very sensitive device Capable to measure immediate leachable amount Conventional methods CANT distinguish Convention al methods CAN distinguish

39 SUMMARY The actual glucose skin transport mechanisms all the way up to the patch membrane are yet to be determined Health-Chems TD-G system is assumed to function based on basic reverse transdermal mechanisms. Health-Chems glucose reaction membrane is extremely sensitive (only small and finite glucose amounts are required to generate enzymatic color change) Measures outside of conventional understanding of transdermal transport modality (steady state flux vs. within lag time interval) Requires New Thinking Approach

40 TD Glucose TM Monitoring System Technical Review

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