The ability to predict crystal growth habits is an important component of drug design, enabling a targeted sweep of optimal growth conditions that confer desirable properties. This article presents an investigation into the shape of olanzapine crystals grown from various solvents, exemplifying how mechanistic models of spiral growth can be applied to small molecule therapeutics. Olanzapine is recognized as the most effective treatment for schizophrenia, but a mechanistic treatment of the underlying crystal growth has yet to be established. We model spiral growth of olanzapine form I from five solvents (acetone, ethyl acetate, toluene, methyl isobutyl ketone, and n-butyl acetate), considering a dimeric growth unit and periodic bond chains consisting of interdimer bonds. The centrosymmetric dimers are stabilized by multiple C–H···π contacts. The {1 0 0} face family dominates the predicted crystal habits, in agreement with our experiments; this morphology stems from the in-plane hydrogen bonds that are exposed on the {1 0 0} surface. The close agreement between predicted morphologies and experimental determinations lends support to the hypothesis that olanzapine grows as a dimer from these solvents. This mechanistic treatment can be readily applied to other compounds.

To continue the realization of new therapeutics, a more diverse range of solid forms is being considered. Synthetic modalities are broadening beyond simple organic molecules to more complicated structures, including organic salts, cocrystals, and solvates. As in all crystalline applications, engineering the morphology of such systems remains an important consideration, but traditional in silico approaches require further development to become capable of accurately describing these systems. A necessary, but not sufficient, condition to enact mechanistic crystal growth models is to calculate and organize solid-state interactions between growth units. The typical software framework for acquiring this information is to apply crystallographic symmetry operations to generate a unit cell from the asymmetric unit. While this approach is feasible for systems where the asymmetric unit corresponds to the growth unit itself, many systems do not satisfy this criterion, particularly the emerging therapeutic solid forms. By redesigning the input preparation software framework, we can build a description of the solid-state interactions that is independent of the asymmetric unit and applicable to any crystallographic complexity. We demonstrate the application of this method to three organic molecular crystals with crystallography of varying degrees of complexicty. The studied systems are naphthalene (Z′ = 0.5), benzoic acid (Z′ = 1), and tazofelone (Z′ = 2), respectively (where Z′ is the number of molecules in the asymmetric unit). This new software framework lays the groundwork for rapid in silico habit predictions of organic salts, cocrystals, and solvates.

Purpose The study aims to use cone beam computed tomography (CBCT) to (1) define the virtual valid length of pterygoid implants in maxillary atrophic patients from the prosthetic prioritized driven position and (2) measure the implant length engaged in the pterygoid process according to the HU difference of the pterygoid maxillary junction. Materials and methods Virtual pterygoid implants were planned with CBCT of maxillary atrophic patients in the software. The entry and angulation of the implant were planned according to the prosthetic prioritized driven position in the 3D reconstruction image. The planned implant length and the valid length defined as the implant between the pterygoid maxillary junction and pterygoid fossa were recorded. The relationship between the implant and sinus cavity was also evaluated. Results A total of 120 CBCT samples were enrolled and virtually planned. The mean age of the patients was 56.2 ± 13.2 years. One hundred and sixteen samples could successfully place virtual implants according to the criterion. The mean implant length and mean implant length beyond the pterygoid maxillary junction were 16.3 ± 4.2 mm (range, 11.5–18 mm) and 7.1 ± 3.3 mm (range, 1.5–11.4 mm), respectively. Ninety percent of virtually planned implants had a close relationship with the sinus cavity, and implants exhibited longer lengths when they had no relation with the sinus. Conclusion From a prosthetic prioritized driven position with fixed entry and angulation, pterygoid implants achieve adequate bone anchorage length beyond the pterygoid maxillary junction. Due to the individual anatomy and the volume of the maxillary sinus, the implants presented a different positional relationship with the maxillary sinus. Graphical Abstract