Online Resource:

Comparative Pharmacokinetics of PAMAM-OH dendrimers and HPMA copolymers in Ovarian-Tumor-bearing mice

S. Sadekara,b#, O. Linaresc#, GJ. Nohg , D. Hubbardb,d, A. Raya,b, M. Janát-Amsburya,b,e, C. M. Petersona,b,e, J. Facellib,c,f*, and H. Ghandeharia,b,d*

#Authorscontributedequallytothework

*email correspondence: ,

Department of aPharmaceutics and Pharmaceutical Chemistry, bCenter for Nanomedicine, Nano Institute of Utah, cBiomedical Informatics, dDepartment of Bioengineering, eDepartment of Obstetrics and Gynecology, fCenter for High Performance Computing, University of Utah, Salt Lake City, Utah, 84108, USA,gDepartment of Clinical Pharmacology and Therapeutics/Anesthesiology and Pain Medicine Asan Medical Center, University of Ulsan College of Medicine, Republic of Korea.

  1. Synthesis of HPMA copolymer (131 kDa)

The comonomersN-(2-hydroxypropyl)methacrylamide (HPMA), N-methacryloyl-glycylglycyl-thiazolidine-2-thione (MA-GG-TT) and N-methacryloyltyrosinamide (MA-Tyr-CONH2) were synthesized by previously reported procedures [1, 2]. To synthesize the high molecular weight HPMA copolymer poly(HPMA-co-(MA-GG-TT)-co-(MA-Tyr-CONH2), the comonomers HPMA (93 mole %), MA-GG-TT (5 mole %) and MA-Tyr-CONH2 (2 mole %) were copolymerized by free radical precipitation copolymerization with azobisisobutyronitrile (AIBN) as the initiator at 500C for 24 hours using methanol as the solvent. Molecular weight was controlled by varying concentration of initiator and monomers in solution. The copolymer was reacted with ethanolamine to yield hydroxyl-terminated side chains.

  1. Biodistribution of polymers:

Detailed biodistribution of PAMAM-OH dendrimers and HPMA copolymers (26 and 52 kDa) is reported in Ref [3]. In addition, we added a third HPMA copolymer (131 kDa), chemically similar to the other HPMA copolymers under study and comparable in molecular weight to G7.0-OH. The biodistribution of this additional HPMA copolymer (131 kDa) is reported below (Figure S1) along with its accumulation in the liver and the kidney in comparison to other polymers under study (Figure S2 and S3).

Figure S1. Percentage of injected dose / g of tissue for HPMA copolymer (131 kDa) in principal organs; Values are Mean +/- SEM; n=3 for 5 minute, 30 minute, 2 hour; n=4 for 6 hour; n=5 for 1 week

Figure S2. Percentage of injected dose / g of kidney tissue for PAMAM-OH dendrimers and HPMA copolymers, Values are Mean +/- SEM. *** indicates a statistically significant difference, p < 0.001.

Figure S3. Percentage of injected dose / g of liver tissue for PAMAM-OH dendrimers and HPMA copolymers, Values are Mean +/- SEM. *** indicates a statistically significant difference, p < 0.001.

Kidney and liver accumulation of HPMA copolymer (131 kDa) was comparable to the PAMAM-OH dendrimer of similarmolecular weight (G7.0-OH).

III.Bloodcompartmental modeling:

Table S1.Akaike Information Criterion (AIC) for compartmental model analysis of PAMAM-OH dendrimers and HPMA copolymers

Polymer / AIC
One- compartment model / AIC
Two- compartment model
G5.0-OH / -4.16 / -78.41
G6.0-OH / -17.42 / -77.87
G7.0-OH / -24.63 / -43.61
HPMA copolymer (26 kDa) / -5.23 / -74.08
HPMA copolymer (52 kDa) / -8.42 / -62.57
HPMA copolymer (131 kDa) / -29.06 / -47.66

AIC was computed using Winnonlin® Version 2.1 for compartmental analysis

The AIC values (Table S1) indicated that a two-compartmental model with bolus input was a better fit for the polymer biodistribution data as compared to a one compartmental model with bolus input.

  1. Renal Clearance

Renal clearance was calculated from urine data collected over time using the following equations:

(1)
(2)

ClR: Renal clearance

AUC blood, 0-ti: Area under the blood concentration-time curve of the polymer

U, ti: Extent of accumulation of polymer in urine at time ti

  1. Polymer Interaction with Bovine Serum Albumin:

Stock solutions of BSA (10 μmol/L) and polymers (160 μmol/L) were prepared in phosphate buffer saline (PBS: 150 mmol/l NaCl, 1.9 mmol/l NaH2PO4, 8.1 mmol/l Na2HPO4, pH 7.4). Polymers were serially diluted to study the interaction of PAMAM-OH dendrimers and HPMA copolymers with BSA at a concentration range of 2.5-80 μmol/L for the polymers and 5μmol/L for BSA [4-6]. After 30 minute incubation at room temperature, sample solutions were measured for fluorescence quenching in a 96 well black polymer BTM P-D-L plate (NalgeNunc International, Rochester, NY) with opaque walls for wells. The spectrofluorometer used was SpectraMax® M2 (Molecular Devices Corporation, Sunnyvale, CA). The excitation wavelength employed was 280 nm and the emission spectra were recorded from 300 to 500 nm. Quenching data was collected for BSA and polymers alone and for BSA upon addition of each polymer at varying concentrations. The fluorescence intensity at the absorption maximum (λmax = 380 nm) was noted in presence and absence of quenching agent (BSA) and plotted as per the Stern-Volmer equation:

Fo = Fluorescence intensity of BSA in absence of quencher (polymer)

F = Fluorescence intensity of BSA in presence of quencher (polymer)

Ksv = Quenching coefficient

[Q] = concentration of quencher (polymer)

Table S2.Quenching coefficients for the interaction of PAMAM-OH dendrimers and HPMA copolymers with bovine serum albumin.

Polymer / Ksv
G5.0-OH (29 kDa) / -0.0001
G6.0-OH (58 kDa) / 0.0042
G7.0-OH (117 kDa) / 0.0107
HPMA copolymer(26 kDa) / -0.0016
HPMA copolymer (52 kDa) / 0.0059
HPMA copolymer (131 kDa) / 0.0064

Ksv: Quenching coefficient of the interaction of bovine serum albumin with the quenching agent.

Serum albumin is a major component of the soluble proteins present in plasma [7]. Bovine serum albumin has two tryptophan residues (Trp-134 and Trp-212) that possess intrinsic fluorescence. This fluorescence is sensitive to the presence of a quenching agent in the vicinity of the BSA molecule. The extent of fluorescence quenching is known to be indicative of the binding affinity of the quenching agent to BSA. Therefore, the quenching coefficient (Ksv) is indicative of the interaction of the polymer with bovine serum albumin (BSA) [8]. The higher the Ksv value, the greater is the interaction of the polymer with BSA. All of the polymers had very low Ksv values close to zero, suggesting that these polymers interacted minimally with bovine serum albumin (Table S2).

  1. Blood concentration-time profile and terminal blood half-life

Polymer / Equation governing blood concentration-time profile / Terminal half-life (h)
G5.0-OH (29 kDa) / Cp = 0.68 e-8.86t + 0.004 e-0.12t / 6.36
G6.0-OH (52 kDa) / Cp = 0.68 e-34.75t + 0.004 e-0.15t / 4.49
G7.0-OH (117 kDa) / Cp = 0.68 e-50.53t + 0.004 e-0. 2t / 3.4
HPMA copolymer (26 kDa) / Cp = 0.68 e-6.95t + 0.004 e-0.16t / 4.23
HPMA copolymer (52 kDa) / Cp = 0.68 e-25.75t + 0.004 e-0.52t / 1.34
HPMA copolymer (131 kDa) / Cp = 0.68 e-11.3t + 0.004 e-0.05t / 12.78

Note that terminal half-life is a function of both blood clearance and peripheral distribution. Hence a long terminal blood half-life can be attributed to larger volume of distribution or smaller blood clearance or both.Therefore, terminal half-life is not the most robust parameter to assess the ability of the body to eliminate the polymer. On the other hand, blood clearance expresses the ability of the body to eliminate the polymer. Hence, blood clearance has been used to correlate the blood pharmacokinetics to MW/Rh of polymers

  1. Blood-tumor link model

Equations describing the Blood-Tumor Link model (Figure 1):

Concentration profile of the central blood compartment (Cp) was modeled using the following equation:

Concentration profile of tumor compartment-1 (Ct1) was modeled using the following equation:

Concentration profile of tumor compartment-2 (Ct1) was modeled using the following equation:

Concentration profile of peripheral fast distribution compartment (Cf) was modeled using the following equation:

Initial conditions:

Cf(0) = Ct1(0) = Ct2(0) = 0

Cp(0) = Dose of polymer / Blood volume

Assumptions:

1.It was assumed that the distribution of polymer in each of the compartments was instantaneous and homogenous.

2.The inter-compartmental rate constants were assumed to be first order.

Optimization code for Global curve fitting of experimental blood and tumor:

The generalized methodology of solving a set of simultaneous first order linear differential equations with unknown coefficients involves utilizing linear optimization techniques in finding the least square fit to the observed experimental data. In this specific case, we have fixed constants K1, K2 and K3 while optimizing K4, K5 and K6 to obtain the desired best fit. Due to the complexity of the problem, an unconstrained search for global minimum is often challenging and time intensive. Therefore, to circumvent this issue, we have used the Optimization toolbox in Matlab® software that offers routines for searching constrained minimum values of multivariable scalar functions with intelligible initial estimates. The algorithm starts with a user supplied initial guess on (K4, K5, K6) and solves the set of differential equations with known initial conditions (namely, blood and tumor compartment 1 and 2 concentrations at time t=0). It then determines the absolute squared error normalized to the experimental value for each data point in every concentration set (Cp, Ct1 and Ct2). This is given by,

Where Yp, Yt1 and Yt2 are the blood and tumor compartment 1 and 2 concentrations at each time points tk, calculated by solving the set of differential equations based on present values of (K4, K5, K6) and eventually summed over all measured time points. This error is minimized using a constrained linear optimization tool in Matlab® that iterates through all possible combinations of (K4, K5, K6) under pre-specified lower and upper bounds on K4, K5 and K6 to determine the best fit.

References:

1. Strohalm J, Kopecek J. Poly N-(2-hydroxypropyl) methacrylamide. 4. Heterogeneous polymerization. Angew Makromol Chem. 1978;70:109-18.

2. Šubr V, Ulbrich K. Synthesis and properties of new N-(2-hydroxypropyl) methacrylamide copolymers containing thiazolidine-2-thione reactive groups. React Funct Polym. 2006;66(12):1525-38.

3. Sadekar S, Ray A, Janat-Amsbury M, Peterson C, Ghandehari H. Comparative biodistribution of PAMAM dendrimers and HPMA copolymers in ovarian-tumor-bearing mice. Biomacromolecules. 2011;12(1):88-96.

4. Klajnert B, Bryszewska M. Fluorescence studies on PAMAM dendrimers interactions with bovine serum albumin. Bioelectrochemistry. 2002;55(1-2):33-5.

5. Klajnert B, Stanisawska L, Bryszewska M, Paecz B. Interactions between PAMAM dendrimers and bovine serum albumin. BBA-Proteins Proteom. 2003;1648(1-2):115-26.

6. Mandeville J, Tajmir-Riahi H. Complexes of dendrimers with bovine serum albumin. Biomacromolecules. 2010;11(2):465-72.

7. Owens III DE, Peppas NA. Opsonization, biodistribution, and pharmacokinetics of polymeric nanoparticles. Int J Pharm. 2006;307(1):93-102.

8. Lakowicz JR, Masters BR. Principles of fluorescence spectroscopy. J Biomed Opt. 2008;13:029901.