Poly(lactic-co-glycolic acid) (PLGA)
has garnered
considerable attention as a versatile platform for the delivery of
active pharmaceutical ingredients (APIs). In the field of API delivery,
the glass transition temperature (T
g
) is widely recognized as a fundamental predictor of drug release
kinetics from PLGA formulations. Despite making significant progress
in understanding the qualitative trends and general effects of multiple
molecular parameters on the glass transition properties of PLGA, accurately
predicting the T
g
value
of a PLGA with a specific molecular weight and composition remains
a challenge. One factor that has previously been overlooked is the
contribution of statistical monomer sequence distribution to the T
g
of PLGA. To address this
research gap, we employed a novel Feed Rate-Controlled Polymerization
(FRCP) technique to synthesize PLGA homopolymers with a comparable
molecular weight and varying degrees of repeat unit (lactate (L, repeat
unit A) and glycolate (G, repeat unit B)) sequence uniformity (uniform
vs gradient PLGA) at different monomer compositions (lactide/glycolide
(LA/GL) ratios). This allowed us to systematically investigate the
effect of LA/GL sequence distribution on the glass transition properties
of PLGA. We observed a significant negative deviation (<∼8
K) from the predictions of the Fox equation in the T
g
vs copolymer composition plot, suggesting
the presence of a repulsive interaction between the LA and GL monomers.
The experimental T
g
data
and the measures of monomer sequence length obtained in our study
exhibited quantitative agreement with the predictions of both the
Johnston theory (based on the free volume concept) and the Barton
theory (based on the configurational entropy concept). Based on our
findings, we propose that by considering the copolymer composition
and monomer dyad or tetrad/triad distribution, it is possible to reasonably
predict the T
g
of a PLGA
material using the alternating dyad glass transition values (T
gAB
or T
gAABB
, respectively) obtained in our study,
without the need for adjustable parameters.