Mark-Houwink PLGA Linearity Estimator

Lactide Content:

The majority of PLGA type polymers are linear in nature, with the exception of those generated using polyfunctional initiators, such as glucose, or those for which specific chemical modifications have been applied to achieve specific architectures. Through the use of gel-permeation-chromatography quaternary detection (GPC-4D), Akina, Inc. has developed techniques around measuring the branching status of PLGAs by leveraging the reduction in viscosity caused by reduced hydrodynamic radius present for a branched PLGA as compared to its linear counterpart1,2. Doing this requires carefully establishing critical parameters including the dn/dc as well as the drainage factor, both of which are affected by the lactide:glycolide (LA:GA) ratio of PLGA3,4.

As a quick, rule-of-thumb, if the intrinsic viscosity of a sample measured by the same methodology matches or exceeds that of a linear comparator at a given molecular weight which is representative of the average molecular weight of the sample, then it is highly probable that the sample is linear in structure. Utilizing data obtained from PLGA linear standards generated at Akina, Inc, composite Mark-Houwink profiles were generated for PLGA 50:50, 75:25, and 100:0 (PDLLa).

Table 1. Data used in Mark-Houwink calculations as obtained by GPC-4D analysis at Akina, Inc.

Polymer Standard Molecular Weight
(Mn, Mw, Mz)
Intrinsic Viscosity
at (Mn, Mw, Mz)
PLGA 50L-S Lot #180329RAI-A 5834 10.985
  8303 13.48
  10890 15.74
PLGA 50L-M Lot #180406RAI-A 16280 20.63
  23790 25.02
  29700 27.803
PLGA 50L-H Lot #190314RAI-A 42620 37.926
  52530 42.13
  64490 46.949
PLGA 50L-H-E Lot #240202RAI-A) 34880 32.49
  45730 37.25
  58560 42.47
PLGA 50L-H-E Lot #201210RAI-A 49038 40.012
  59050 43.799
  72630 48.617
PLGA 75L-M Lot #180323RAI-A 16290 21.624
  25370 27.97
  33700 32.668
PLGA 75L-S Lot #180410RAI-A  12180 17.52
  17830 22.04
  22420 25.121
PLGA 75L-H Lot #180313RAI-B 76170 57.63
  96330 65.14
  110500 69.288
PLA 100L-S Lot #180312FAJ-A 8142 12.888
  15890 18.75
  39590 36.635
PLA 100L-M Lot #180306FAJ-A 24900 27.819
  33900 33.69
  40400 37.381
PLA 100L-H Lot #180302RAI-A 103200 69.074
  132700 78.942
  190200 96.207

This data was plotted to form composite plots for indicated PLGAs (La:Ga ratio).

Figure 1. Mark-Houwink plots of PLGA 50L, 75L, and 100L, respectively.


From this the following Mark-Houwink Parameters were derived for linear polymers. Note that the Mark-Houwink profile of each GPC run naturally varies due to normal experimental error and these just provide a general average of the profile across a series of representative linear runs. Additionally, the standard error of the data from the regression was calculated based on the R2 value. For this, the following equations were applied.

Mark-Houwink equation: Intrinsic viscosity = K*(Molecular Weight)a

Standard Error: SE = ((1-R2)/N-2)(1/2)

PLGA (La:Ga) Slope constant (K) Exponent (a) Standard error
50:50 0.0592 0.6017 0.0194
75:25 0.0452 0.6334 0.926
100:0 0.0376 0.649 0.926

Based on this data, an estimation as to whether a sample is primarily comprised of linear PLGA or possibly branched based on the number average molecular weight (Mn) and the intrinsic viscosity at number average molecular weight ([η]n (mL/g)) can be found using the calculator above to determine if the samples viscosity is reduced relative to known linear standards within normal experimental error (2 x standard error lower, 95% bounded range).


Like all measurements, these parameters are susceptible to experimental error. Additionally, this only applies to data obtained under the conditions present in GPC-4D (acetone, 25 C, flow conditions, Mn fraction specifically) and should not be extrapolated to inherent viscosity obtained using other methods. If you would like to discuss branch measurements of your samples, please contact us.


  1. Justin Hadar, Sarah Skidmore, John Garner, Haesun Park, Kinam Park, Yan Wang, Bin Qin, Xiaohui (Jeff) Jiang, Darby Kozak “Method matters: Development of characterization techniques for branched and glucose-poly(lactide-co-glycolide) polymers”, Journal of Controlled Release Volume 320, 10 April 2020, Pages 484-494.
  2. Hadar, Justin, Sarah Skidmore, John Garner, Haesun Park, Kinam Park, Yan Wang, Bin Qin, and Xiaohui Jiang. “Characterization of branched poly (lactide-co-glycolide) polymers used in injectable, long-acting formulations.” Journal of Controlled Release (2019).
  3. J. Hadar, J. Garner, S. Skidmore, H. Park, K. Park, Y. K. Jhon, Y. Wang. “Correlation Analysis of Refractive Index (dn/dc) for PLGAs with Different Ratios of Lactide to Glycolide” Scientific Poster presented at 2018 annual meeting of Controlled Release Society
  4. J. Hadar, J. Garner, S. Skidmore, H. Park, K. Park, B. Qin, X. Jiang, Y. Wang. “Analysis of the branch units of glucose-poly(lactide-co-glycolide) in Sandostatin® LAR formulation” Scientific Poster presented at 2019 annual meeting of Controlled Release Society