Method and its Composition for encapsulation, stabilization, and delivery of siRNA in Anionic polymeric nanoplex: An In vitro- In vivo Assessment

Small interfering RNA (siRNA) are synthetic RNA duplex designed to specifically knockdown the abnormal gene to treat a disease at cellular and molecular levels. In spite of their high potency, specificity, and therapeutic potential, the full-fledged utility of siRNA is predominantly limited to in vitro set-up. Till date, Onpattro is the only USFDA approved siRNA therapeutics available in the clinic. The lack of a reliable in vivo siRNA delivery carrier remains a foremost obstacle towards the clinical translation of siRNA therapeutics. To address the obstacles associated with siRNA delivery, we tested a dendrimer-templated polymeric approach involving a USFDA approved carrier (albumin) for in vitro as well as in vivo delivery of siRNA. The developed approach is simple in application, enhances the serum stability, avoids in vivo RNase-degradation and mediates cytosolic delivery of siRNA following the endosomal escape process. The successful in vitro and in vivo delivery of siRNA, as well as targeted gene knockdown potential, was demonstrated by HDAC4 inhibition in vitro diabetic nephropathy (DN) podocyte model as well as in vivo DN C57BL/6 mice model. The developed approach has been tested using HDAC4 siRNA as a model therapeutics, while the application can also be extended to other gene therapeutics including micro RNA (miRNA), plasmids oligonucleotides, etc.

feed section. The screened process variable with their outcomes as stated in Table S1.  Results are represented as mean ±S.D (n=3).

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It was found that the contribution of albumin concentration, ethanol concentration and agitation 54 speed towards the resultant particle size was found 8.37 %, 50.47 %, and 16.04 %, respectively as 55 shown in Fig. S1A. The p-value for the two-level Five-factor (2 5 ) full factorial design model for 56 particle size was 0.0046 (R 2 value: 0.8989), which indicated that the model was significant for 57 process outcomes. Notably, the p-value for albumin concentration (0.0806), ethanol volume 58 (0.6132) and addition rate (0.6132) was larger than 0.05 and hence was found non-significant to 59 the applied model. Therefore, it suggested that albumin concentration, ethanol concentration, and 60 agitation speed has maximum influence on the particle size of nanoplex.

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In context to PDI, the contribution of albumin concentration, ethanol volume, and agitation speed 62 (rpm) was found 21.19 %, 32.71 %, and 7.32 %, respectively (Fig. S1B). However, p-value and 63 R 2 value for the model obtained by applying ANOVA were 0.0254 and 0.9607, respectively 64 signifies that the applied model was significant to process outcomes. On another hand, the p-value 65 for ethanol volume (0.3943), rate of addition (0.2888) and agitation speed (0.1623) were found to 66 be greater than 0.05, which infers that it does not significantly affect on the PDI of the resultant 67 nanoplex. Similar to particle size, in the case of PDI, albumin concentration, ethanol concentration 68 and agitation speed have shown the maximum impact on PDI of nanoplex (Fig. S1B). Therefore, 69 these process parameters need more optimization to attain the targeted size and PDI.

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In summary, taking lad from the QbD-driven risk factor analysis using 2-level full factorial design, 71 ethanol volume and rate of addition were kept constant, since they had no a significant impact on 72 particle size and PDI of nanoplex. The ethanol volume and rate of addition were kept constant at 73 4 ml and 50 μl/min, respectively. The albumin concentration (%w/v), ethanol concentration (%v/v) 74 and agitation speed (rpm) were selected as CQA for in-depth three-factor at three-level (3 3 ) Box-

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Behnken design due to their direct and significant impact on the particle size and PDI of nanoplex.

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It may be noted that three factors at three-level Box-Behnken design have been selected for QbD Particle size (B) PDI.

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The selected process parameters (Table S2) were tested by applying Box-Behnken design to assess 84 the ideal process conditions for attaining the nanoplex of the desired size. It may be noted that the  Using Box-Behnken design, the polynomial equation for particle size was also obtained as follows 104 to assess the influence of individual process parameters on the process outcome:  interaction curves of the surface response plot (Fig. S2C). 146 Similarly, the 3D-surface response contour plots inferred that at lesser agitation speed (500 rpm) 147 obtained desirability region was very less (blue region in Fig. S2D). Whereas, as shown in that is predicted to yield nanoplex of particle size 67.044 nm and 0.268 PDI (Table S3 and

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This effect was further confirmed via pH-responsive change in the surface zeta potential and 360 particle size of nanoplex (Supplementary Figure S19). This pH-responsive and endosomal 361 escape effect was primarily due to dendrimeric template of nanoplex not because of the loaded 362 siRNA. It confirmed that pH has no notable impact on siRNA. The observed effect can be ascribed 363 to the protonation behavior of dendrimeric template present in the nanoplex 12 .  Figure 5D of the main manuscript.    responses. Moreover, ANOVA was also applied to evaluate the significance of model and factors.

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The interactions between the selected process parameters were also evaluated by analyzing the 433 contour plots and reach conclusive remarks.