Supporting Information

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1 Supporting Information Comparative Assessment of Active Targeted Redox Sensitive Polymersomes Based on ppegma-s-s-pla Diblock Copolymer with Marketed Nanoformulation Chetan Nehate ab, Aji Alex Moothedathu Raynold ab, V. Haridas c, Veena Koul ab * a Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi , India b Biomedical Engineering Unit, All India Institute of Medical Sciences, New Delhi , India. c Department of chemistry, Indian Institute of Technology Delhi, New Delhi , India *Corresponding Author Tel: veenak_iitd@yahoo.com S1

2 S1: Results and discussion for synthesis of 2-((2-hydroxyethyl)-disulfanyl)ethyl-2-bromo- 2-methyl propanoate The lactide ring opener substrate, 2-((2-hydroxyethyl)-disulfanyl)ethyl-2-bromo-2-methyl propanoate was synthesized by reacting 2-bromoisobutyryl bromide with 2-hydroxyethyl disulfide. The single bromo-functionalized 2-hydroxyethyl disulfide compound was separated from other impurities such as double bromo-functionalized 2-hydroxyethyl disulfide and unreacted 2-hydroxyethyl disulfide by using silica gel chromatography. The elute was continuously monitored by thin layer chromatography using mobile phase (70:30 hexane and ethyl acetate). The obtained elute was concentrated on rotavapor to get the pale brown oily product. The compound was characterized by 1 H NMR (Figure S2) and HR-MS (Figure S3). S2: Results and discussion for synthesis of polylactide macroinitiator (Br-S-S-PLA) The polylactide macroinitiator was developed by ring opening polymerization of lactide by 2- ((2-hydroxyethyl)-disulfanyl)ethyl-2-bromo-2-methyl propanoate with in the presence tin (II) 2-ethylhexanoate as a catalyst. The developed macroinitiator was thoroughly characterized by 1 H NMR and GPC. In 1 H NMR spectra of macroinitiator displayed the presence of cystamine unit with the 2-brmoisobutyryl group attached. The multiplet peak at δ and δ confirmed the presence of PLA unit in polymer chain with peak integration ratio of 3:1 (Figure S4). The singlet peak at δ 1.94 relates the geminal methyl protons of 2-hydroxyl ethyl bromide. The multiplet peak at δ 2.94 depicts the presence of disulfide bond adjacent methylene protons, while the peak at δ 2.39 corresponds to the terminal methylene groups of the 2- hydroxyethyl disulfide linkage. Thus 1 H NMR confirmed the successful synthesis of PLA macroinitiator. The number average molecular weight (Mn) of macroinitiator based on its 1 H NMR integration was found to be ~9000 Da. While GPC showed the Mn as Da with PDI of 1.32 (Figure S5). S2

3 Figure S1. The synthesis scheme of folic acid conjugated poly(poly ethylene glycol) methacrylate polylactide diblock copolymer. S3

4 Figure S2. 1 H NMR spectra (400 MHz, CDCl3, δ (ppm)) of 2-((2- Hydroxyethyl)disulfanyl)ethyl-2-bromo-2-methyl propanoate. S4

5 Figure S3. HR-MS spectra of 2-((2-Hydroxyethyl)disulfanyl)ethyl-2-bromo-2-methyl propanoate. S5

6 Figure S4. 1 H NMR spectra (400 MHz, CDCl3, δ (ppm)) of bromo-terminated polylactide macroinitiator (Br-S-S-PLA) S6

7 Figure S5. GPC spectra of bromo-terminated polylactide macroinitiator (Br-S-S-PLA). S7

8 Figure S6. 1 H NMR spectra (400 MHz, CDCl3, δ (ppm)) of poly[poly(ethylene glycol) methacrylate]-polylactide diblock copolymer, [(PEGMA)n-S-S-PLA]. S8

9 Figure S7. GPC spectra of poly[poly(ethylene glycol) methacrylate]-polylactide diblock copolymer. S9

10 Figure S8. XPS scanning spectrum of polymersomes, (A) folic acid conjugated [(PEGMA)n- S-S-PLA] copolymer and (B) [(PEGMA)n-S-S-PLA] copolymer. S10

11 Figure S9. UV-visible spectra of folic acid, poly[poly(ethylene glycol) methacrylate]- polylactide diblock copolymer (PLA-PEGMA) and folic acid conjugated poly[poly(ethylene glycol) methacrylate]-polylactide diblock copolymer, (PLA-PEGMA-FA). S11

12 Figure S10. FTIR spectra of folic acid, poly[poly(ethylene glycol) methacrylate]-polylactide diblock copolymer (PLA-PEGMA), and folic acid conjugated poly[poly(ethylene glycol) methacrylate]-polylactide diblock copolymer (PLA-PEGMA-FA). S12

13 Table S1. Optimized freeze drying cycle for lyophilization of PLA-DOX-FA polymersomes. Freeze Drying Ramp/ Temperature Vacuum Time Steps Hold 25 C - 10 H 0 C - 30 R Thermal Treatment 0 C - 30 H -45 C - 60 R -45 C H Freeze Temp. -55 C Extra freezing steps Additional Freeze time 120 min Condenser set point -45 C Vacuum set point 500 mtorr -40 C 200 mtorr 60 R -40 C H -20 C R Drying steps -20 C H Primary Drying and 0 C R Secondary Drying 0 C H 25 C R 25 C H Post Heat Period 25 C S13

14 Table S2. CHNS study of PLA-PEGMA and PLA-PEGMA-FA using elemental analyzer a. Polymer Composition of elements (%) C H N S PLA-PEGMA ± ± ± ± 0.04 PLA-PEGMA-FA ± ± ± ± 0.12 ( a Mean ± SD, n = 3) S14

15 Table S3: Levels of independent factors used in experiments Factor Code A B Independent Factor Drug:Polymer ratio (w/w) Solvent:Non solvent ratio (v/v) (-α) Levels (+α) Table S4. Central composite optimization design for preparation of polymersomes. Formulation code Drug:Polymer ratio (w/w) (Coded) Solvent:Nonsolvent ratio (v/v) (coded) Drug:Polymer ratio (w/w) (Non-coded) Solvent:Nonsolvent ratio (v/v) (Noncoded) N N N N N N N N N N N N S15

16 Figure S11. Predicted versus actual plots for, (A) Drug loading (%), (B) Particle size (nm) and (C) PDI. S16

17 S3. Interpretation of responses by Expert-Design software S3.1. Drug loading (%) A quadratic model was suggested by the Design-Expert 11 software for loading efficiency. The model proposed the following polynomial equation for determination of percentage loading efficiency. Y1 = A B 0.647AB 0.548A B 2 Where, Y1 is percent drug loading, A is drug:polymer ratio (w/w) and B is solvent:non-solvent ratio (v/v). Table S3.1.1 Analysis of variance table for drug loading (%). Source Sum of squares df Mean square F-value p-value Model < Ѱ A-A < B-B < AB A B < Residual Lack of Fit # Pure Error Cor Total Where, A: Drug:polymer ratio (w/w), B: Solvent:Non-solvent ratio (v/v), Ѱ highly significant and # not significant. The Model F-value of implies the model is significant. There is only a 0.01 % chance that an F-value this large could occur due to noise. P-values less than 0.05 indicate model terms are significant. In this case, A, B, AB, A², and B² are significant model terms. Values greater than 0.1 indicate the model terms are not significant. S17

18 The Lack of Fit F-value of 1.56 implies the Lack of Fit is not significant relative to the pure error. There is a % chance that a "Lack of Fit F-value" this large could occur due to noise. Non-significant lack of fit is good. Table S Fitting statistics for drug loading (%) Fitting statistics Standard deviation R Mean Adjusted R Coefficient of variation (%) Predicted R Adeq Precision The predicted vs actual values plot depicted good correlation with R (Figure S9A). The adjusted R 2 of was in the reasonable range with predicted R 2 of Adeq Precision ratio measures signal to noise ratio. Adeq Precision > 4 is desirable for good fitting of data. Our ratio, indicates an adequate signal for proper model fitting. Thus, this model can be used to navigate for desired operational space S3.2. Particle size (nm) A quadratic model was suggested by the software for particle size measurement. The model proposed the following polynomial equation for determination of particle size. Y1 = A B AB A B 2 Where, Y1 is particle size (nm), A is drug:polymer ratio (w/w) and B is solvent:non-solvent ratio (v/v). S18

19 Table S Analysis of variance table for particle size (nm). Source Sum of squares df Mean square F-value p-value Model < Ѱ A-A < B-B AB < A < B < Residual Lack of Fit # Pure Error Cor Total Where, A: Drug:polymer ratio (w/w), B: Solvent:Non-solvent ratio (v/v), Ѱ highly significant and # not significant. The Model F-value of implies the model is significant. There is only a 0.01 % chance that an F-value this large could occur due to noise. P-value less than 0.05 indicate model terms are significant. In this case, A, B, AB, A², and B² are significant model terms. Values greater than 0.1 indicate the model terms are not significant. The Lack of Fit F-value of 7.84 implies there is a 6.23 % chance that a Lack of Fit F-value this large could occur due to noise. Table S Fitting statistics for particle size (nm). Fitting statistics Standard deviation R Mean Adjusted R Coefficient of variation (%) Predicted R Adeq Precision S19

20 The predicted vs actual values plot depicted good correlation with R (Figure S9B). The adjusted R 2 of was in the reasonable range with predicted R 2 of Adeq Precision ratio measures signal to noise ratio. Adeq Precision > 4 is desirable for good fitting of data. Our ratio, indicates an adequate signal for proper model fitting. Thus, this model can be used to navigate for desired operational space S3.3. Polydispersity index (PDI) A quadratic model was suggested by the software for PDI measurement. The model proposed the following polynomial equation for PDI. Y1 = A 0.011B 0.001AB A B 2 Where, Y1 is polydispersity index, A is drug:polymer ratio (w/w) and B is solvent:non-solvent ratio (v/v). Table S Analysis of variance table for PDI. Source Sum of squares df Mean square F-value p-value Model < Ѱ A-A < B-B AB A < B < Residual Lack of Fit # Pure Error Cor Total Where, A: Drug:polymer ratio (w/w), B: Solvent:Non-solvent ratio (v/v), Ѱ highly significant and # not significant. The Model F-value of implies the model is significant. There is only a 0.01 % chance that an F-value this large could occur due to noise. P-values less than 0.05 indicate model terms are significant. In this case, A, B, A², and B² are significant model terms. Values greater than 0.1 indicate the model terms are not significant. The Lack of Fit F-value of 5.29 implies S20

21 the Lack of Fit is not significant relative to the pure error. There is a % chance that a "Lack of Fit F-value" this large could occur due to noise. Table S Fitting statistics for PDI. Fitting statistics Standard deviation R Mean Adjusted R Coefficient of variation (%) Predicted R Adeq Precision The predicted vs actual values plot depicted good correlation with R (Figure S9C). The adjusted R 2 of was in the reasonable range with predicted R 2 of Adeq Precision ratio measures signal to noise ratio. Adeq Precision > 4 is desirable for good fitting of data. Our ratio, indicates an adequate signal for proper model fitting. Thus, this model can be used to navigate for desired operational space S21

22 Table S5. Central circumscribed design (CCD) design for optimization of polymersomes. Independent factors Responses Code Drug:Polymer ratio (w/w) Solvent:Nonsolvent ratio (v/v) Drug loading (%) Particle Size (nm) PDI N N N N N N N N N N N N S22

23 Figure S12. Powder X-ray diffraction (PXRD) scans of (A) Pure DOX, (B) Blank polymersomes, (C) Pure DOX and blank polymersomes physical mixture, (D) PLA-DOX-FA polymersomes. S23

24 Figure S13. Long term stability DLS data of lyophilized PLA-DOX-FA polymersomes with respect to size and zeta potential, where, (A,B) after 1 month, (C,D) after 2 months and, (E,F) after 3 months. (n = 3) S24

25 Table S6. Drug release kinetics from polymersomes analyzed by regression coefficient method. Sr. No. Release medium Zero Order Hixon- Crowell First Order Higuchi Korsmeyer peppas R 2 R 2 R 2 R 2 R 2 n 1 ph ph 7.4 with 20 µm GSH ph ph 7.4 with 10 mm GSH ph 5 with 10 mm GSH Table S6.1. Drug transport mechanisms and release exponents (n) from Korsmeyer peppas. 1, 2 Release Exponent, n Type of Transport Time Dependence < n < 1 1 n > 1 Fickian diffusion Anomalous transport Case II transport Super case II transport t 1/2 t n-1 time independent t n-1 S4. Interpretation of drug release kinetics The DOX release profiles from DOX loaded polymersomes in different conditions were fitted in various drug release kinetic models such as zero order, Hixon-Crowell, first order, and Higuchi. Korsmeyer peppas model was used to study the release mechanism from polymersomes. A correlation coefficient (R 2 ) was selected to define approximate accuracy of each model. The drug release profile at ph 7.4 and ph 7.4 with 20 μmol GSH followed zero order or Hixon-Crowell model which must be accounted due to slow release of drug either by diffusion or slow erosion of copolymer. The same phenomenon has been reported for other types of biodegradable polymersomes. 3, 4 At ph 5.0 the drug release profile was best fitted with Korsmeyer peppas model following non-fickian diffusion or anomalous transport mechanism (n = 0.961) suggesting interaction of drug molecules, release medium and carrier matrix exist. 5, 6 The drug release profiles at ph 7.4 and ph 5.0 with the presence of 10 mmol GSH were precisely fitted in Korsmeyer peppas model and followed case II transport (n = 1.063) and super case II transport (n = 1.194) respectively. This increase in release exponent (n) in the presence of 10 mmol GSH can be ascribed to the fast degradation of polymer chains due to S25

26 breakage of disulfide linkages in polymersomes depicting enhanced release by complex release mechanism. 7, 8 Figure S14. CLSM images for nuclear localization study of PLA-DOX-FA polymersomes incubated for 8 h in (A) MDA-MB-231, (B) HeLa, and (C) L929 cells. All the images were taken at 60 magnification. S26

27 Figure S15. CLSM images for competition assay of PLA-DOX-FA polymersomes in the presence of free folic acid (1 mmol) in (A) MDA-MB-231, (B) HeLa, and (C) L929 cells. All the images were taken at 60 magnification. S27

28 Figure S16. Reactive oxygen species (ROS) determination of blank polymersomes on MDA- MB-231, HeLa, and L929 cells. (Mean ± SD, n = 3. Where ns indicates not significant, p > 0.05). S28

29 Figure S17. Percent relative body weight changes of animals used during repeated dose toxicity study. (Mean ± SD, n = 6. Where ns indicates not significant p > 0.05). S29

30 Figure S18. Histopathological evaluation of vital organs of mice treated with, (A) control, PBS 7.4 and (B) blank polymersomes. All images were taken at 20 X magnification under bright field illumination. S30

31 Table S7. Serum biochemistry parameters of animals treated with PBS ph 7.4 (control), Blank polymersomes at dose of 100 mg/kg of body weight during the course of 11 days repeated dose toxicity study a Sr. No. Biochemical Parameters b Control Blank polymersomes 1 CK-MB (U/L) 3.46 ± ± AST (U/L) ± ± ALT (U/L) ± ± Urea (mg/dl) ± ± Creatinine (mg/dl) 0.05 ± ± 0.02 ( a Mean ± SD, n = 3. b CK-MB, creatine kinase-mb; AST: alanine aminotransferase; and ALT, aspartate aminotransferase). S31

32 Table S8. Hematological parameters analysis of blank polymersomes treated mice used for toxicological assessment at a repeated dose of 100 mg/kg a. Sr. No. Hematology and serum biochemistry parameters with units Control group (PBS) Blank polymersomes (100 mg/kg ) 1 White blood cells (10 3 /mm 3 ) 7.40 ± ± Lymphocytes (%) ± ± Monocytes (%) ± ± Granulocytes (%) ± ± Lymphocytes (10 3 /mm 3 ) 3.37 ± ± Monocytes (10 3 /mm 3 ) 2.50 ± ± Granulocytes (10 3 /mm 3 ) 1.53 ± ± Red blood cells (10 3 /mm 3 ) 6.50 ± ± Hemoglobin (g/dl) 9.07 ± ± Hematocrit (%) ± ± Mean corpuscular volume (µm 3 ) ± ± Mean corpuscular hemoglobin (pg) ± ± Mean corpuscular hemoglobin concentration (g/dl) ± ± Red cell distribution width (%) ± ± Platelets (10 3 /mm 3 ) ± ± Mean platelet volume (µm 3 ) 7.97 ± ± Procalcitonin (%) 1.14 ± ± Platelet Distribution Width (%) ± ± 1.33 ( a Mean ± SD, n = 3) S32

33 Figure S19. Percent relative body weight changes of tumor bearing mice used during the evaluation of the antitumor efficacy of free DOX, DOXIL and, PLA-DOX-FA polymersomes. (Mean ± SD, n = 6. Where *** indicates not significant p < 0.001). S33

34 Table S9. Statistical P values for serum biochemical parameters of mice groups treated with PBS ph 7.4 (control), free DOX, DOXIL and PLA-DOX-FA polymersomes during tumor regression study a. Biochemical Parameters b Control vs DOX Statistical P values Control vs DOXIL Control vs PLA- DOX-FA DOX vs DOXIL DOX vs PLA-DOX- FA DOXIL vs PLA-DOX- FA CK-MB (U/L) AST (U/L) ALT (U/L) Urea (mg/dl) Creatinine (mg/dl) ( a Mean ± SD, n = 3. b CK-MB, creatine kinase-mb; AST: alanine aminotransferase; and ALT, aspartate aminotransferase) S34

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