As the most popular form of drug delivery, solid form formulations, such as
tablets, are utilised throughout the world, and their development is crucial to delivering
new medicines to market. However, the solid form drug product does not
only require focus on its active pharmaceutical ingredient (API) but also its interactions
with other ingredients (excipients) within the formulation. The compatibility
between the API and excipients plays a critical role in the final drug product performance.
Currently, drug products are being developed using a trial and error approach
to determine the best formulation. The ability to pre-screen API-Excipient
particle interactions would allow formulators to make a more informed decision on
the experimental studies to be carried out, thus reducing the development time and
resources required to get a molecule from discovery to product.
This body of work presents two methodologies for assessing the inter-particulate
interactions between faceted organic crystals, such as those used for drug product
formulations. Previous studies have utilised single probe molecules to computationally
calculate the interactions between the probe and surface, in order to relate
those to the inter-particulate forces. Within this project, an in-silico methodology
has been developed which calculates interactions of opposing crystal slabs, taking
into account approach distance, atomic roughness induced steric repulsions, displacements
and rotation. Maps of the interaction space were produced allowing
identification of the mechanism of surface interaction, all a marked improvement
on single molecular probe methods. This development could aid pre-screening efforts,
and inform solid-state and formulation scientists, of the impact the surface
chemistry can have interactions.
Atomic force microscopy adhesion data has previously been shown to correlate
well with formulation performance. In this study, the facet specific interactions were
measured for the first time and shown to agree with the in silico method. It was
found, not unexpectedly, that micro-surface roughness controlled surface adhesion,
although in silico measurements showed conversely that atomic roughness increased
surface adhesion.
The materials analysed were Paracetamol Form I (Para), � - L-Glutamic acid
(LGA) and � - D-Mannitol due to their varying crystal morphology, surface chemistry,
and ease with which it can be crystallised. Multiple paracetamol facets were
used for adhesive measurements, and a cleaning study was carried out determining
the most effective protocol of cleaning paracetamol surfaces from a topographical
and surface chemistry point of view.
For the in-silico approach, a molecular mechanics (MM) workflow has been developed
and an accompanying analysis tool, allowing high-throughput analysis. It
was found that Para shows higher cohesive behaviour in the presence of DMAN
compared to LGA due to the higher interactions between the hydrophilic surfaces
of DMAN. Surface roughness was found to be inversely correlated to the interaction
energy, except for a few cases where higher roughness equated to more energy
due to the slabs interlocking. Facets (10¯1) and (11¯1) of Para were found to be the
most interactive across Para and DMAN/LGA substrate facets respectively. Finally,
a strong case has been made for using energy distributions to describe facet
interactions, over conventional use of the lowest interaction energy.
Experimentally, for the first time, the adhesion between faceted organic crystals
was measured. Small crystals were mounted onto the end of AFM cantilevers, and
with the orientation of the substrate crystals (also faceted) adjusted, the two crystals
were brought into contact. Forces were measured for the fully indexed Para crystal
giving a ranking of most interactive facets Para/Para : F10¯1 >> F101 > F11¯1.
Similarly to the in-silico results, the (10¯1) was found to be the most adhesive for
Para/Para systems followed by the (101) and (11¯1). As with the in-silico Para was
found to be more cohesive in the presence of DMAN and more adhesive with LGA,
showing a correlation with the model.
The cohesive/adhesive balance analysis and interactive probe ranking were within
agreement between the experimental and computation technique, thus validating
the model and increasing confidence that it can be used to assist in pre-screening
API-Excipient interactions.
