Vegetative fragment production as a means of propagule dispersal for tropical seagrass meadows.

BACKGROUND AND AIMS: Long distance dispersal (LDD) contributes to the replenishment and recovery of tropical seagrass habitats exposed to disturbance, such as cyclones and infrastructure development. However, our current knowledge regarding the physical attributes of seagrass fragments that influence LDD predominantly stems from temperate species and regions. The goal of this paper is to measure seagrass fragment density and viability in two tropical species, assessing various factors influencing their distribution. METHODS: We measured the density and viability of floating seagrass fragments for two tropical seagrass species (Zostera muelleri and Halodule uninervis) in two coastal seagrass meadows in the central Great Barrier Reef World Heritage Area, Australia. We assessed the effect of wind speed, wind direction, seagrass growing/senescent season, seagrass meadow density, meadow location and dugong foraging intensity on fragment density. We also measured seagrass fragment structure and fragment viability; i.e., potential to establish into a new plant. KEY RESULTS: We found that seagrass meadow density, season, wind direction and wind speed influenced total fragment density, while season and wind speed influenced the density of viable fragments. Dugong foraging intensity did not influence fragment density. Our results indicate that wave action from winds combined with high seagrass meadow density increases seagrass fragment creation, and that more fragments are produced during the growing than the senescent season. Seagrass fragments classified as viable for Z. muelleri and H. uninervis had significantly more shoots and leaves than non-viable fragments. We collected 0.63 (±0.08 SE) floating viable fragments 100 m-2 in the growing season, and 0.13 (±0.03 SE) viable fragments 100 m-2 in the senescent season. Over a third (38%) of all fragments collected were viable. CONCLUSION: There is likely to be a large number of viable seagrass fragments available for long distance dispersal. This study's outputs can inform dispersal and connectivity models that are used to direct seagrass ecosystem management and conservation strategies.

Venglustat, a Novel Glucosylceramide Synthase Inhibitor, in Patients at Risk of Rapidly Progressing ADPKD: Primary Results of a Double-Blind, Placebo-Controlled, Phase 2/3 Randomized Clinical Trial.

RATIONALE & OBJECTIVE: Autosomal dominant polycystic kidney disease (ADPKD) is characterized by the formation of multiple kidney cysts that leads to growth in total kidney volume (TKV) and progression to kidney failure. Venglustat is a glucosylceramide synthase inhibitor that has been shown to inhibit cyst growth and reduce kidney failure in preclinical models of ADPKD. STUDY DESIGN: STAGED-PKD was a 2-stage, multicenter, double-blind, randomized, placebo-controlled phase 2/3 study in adults with ADPKD at risk of rapidly progressive disease, who were selected based on Mayo Clinic imaging classification of ADPKD class 1C, 1D, or 1E and an estimated glomerular filtration rate (eGFR) of 30-89.9mL/min/1.73m2. SETTING & PARTICIPANTS: Enrollment included 236 and 242 patients in stages 1 and 2, respectively. INTERVENTIONS: In trial stage 1, the patients were randomized 1:1:1 to venglustat, 8mg; venglustat, 15mg; or placebo. In stage 2, the patients were randomized 1:1 to venglustat, 15mg (highest dose identified as safe and well tolerated in stage 1), or placebo. OUTCOMES: Primary end points were rate of change in TKV over 18 months in stage 1 and eGFR slope over 24 months in stage 2. Secondary end points were eGFR slope over 18 months (stage 1), rate of change in TKV (stage 2), and safety/tolerability, pain, and fatigue (stages 1 and 2). RESULTS: A prespecified interim futility analysis showed that venglustat treatment had no effect on the annualized rate of change in TKV over 18 months (stage 1) and had a faster rate of decline in eGFR slope over 24 months (stage 2). Due to this lack of efficacy, the study was terminated early. LIMITATIONS: The short follow-up period after the end of treatment and limited generalizability of the findings. CONCLUSIONS: In patients with rapidly progressing ADPKD, treatment with venglustat at either 8mg or 15mg showed no change in the rate of change in TKV and a faster rate of eGFR decline in STAGED-PKD despite a dose-dependent decrease in plasma glucosylceramide levels. FUNDING: This study was funded by Sanofi. TRIAL REGISTRATION: Registered at ClinicalTrials.gov with study number NCT03523728.

The STAGED-PKD 2-Stage Adaptive Study With a Patient Enrichment Strategy and Treatment Effect Modeling for Improved Study Design Efficiency in Patients With ADPKD.

Rationale & Objective: Venglustat, a glucosylceramide synthase inhibitor, inhibits cyst growth and reduces kidney failure in mouse models of autosomal dominant polycystic kidney disease (ADPKD). STAGED-PKD aims to determine the safety and efficacy of venglustat and was designed using patient enrichment for progression to end-stage kidney disease and modeling from prior ADPKD trials. Study Design: STAGED-PKD is a 2-stage, international, double-blind, randomized, placebo-controlled trial in adults with ADPKD (Mayo Class 1C-1E) and estimated glomerular filtration rate (eGFR) 45-<90 mL/min/1.73 m2 at risk of rapidly progressive disease. Enrichment for rapidly progressing patients was identified based on retrospective analysis of total kidney volume (TKV) and eGFR slope from the combined Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease and HALT Progression of Polycystic Kidney Disease A studies. Setting & Participants: Target enrollment in stages 1 and 2 was 240 and 320 patients, respectively. Interventions: Stage 1 randomizes patients 1:1:1 to venglustat 8 mg or 15 mg once daily or placebo. Stage 2 randomizes patients 1:1 to placebo or venglustat, with the preferred dose based on stage 1 safety data. Outcomes: Primary endpoints are TKV growth rate over 18 months in stage 1 and eGFR slope over 24 months in stage 2. Secondary endpoints include: annualized rate of change in eGFR from baseline to 18 months (stage 1); annualized rate of change in TKV based on magnetic resonance imaging from baseline to 18 months (stage 2); and safety, tolerability, pain, and fatigue (stages 1 and 2). Limitations: If stage 1 is unsuccessful, patients enrolled in the trial may develop drug-related adverse events that can have long-lasting effects. Conclusions: Modeling allows the design and powering of a 2-stage combined study to assess venglustat's impact on TKV growth and eGFR slope. Stage 1 TKV assessment via a nested approach allows early evaluation of efficacy and increased efficiency of the trial design by reducing patient numbers and trial duration. Funding: This study was funded by Sanofi. Trial registration: STAGED-PKD has been registered at ClinicalTrials.gov with study number NCT03523728.

Patients with Protein-Truncating PKD1 Mutations and Mild ADPKD.

BACKGROUND AND OBJECTIVES: Progression of autosomal dominant polycystic kidney disease (ADPKD) is highly variable. On average, protein-truncating PKD1 mutations are associated with the most severe kidney disease among all mutation classes. Here, we report that patients with protein-truncating PKD1 mutations may also have mild kidney disease, a finding not previously well recognized. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: From the extended Toronto Genetic Epidemiologic Study of Polycystic Kidney Disease, 487 patients had PKD1 and PKD2 sequencing and typical ADPKD imaging patterns by magnetic resonance imaging or computed tomography. Mayo Clinic Imaging Classification on the basis of age- and height-adjusted total kidney volume was used to assess their cystic disease severity; classes 1A or 1B were used as a proxy to define mild disease. Multivariable linear regression was performed to test the effects of age, sex, and mutation classes on log-transformed height-adjusted total kidney volume and eGFR. RESULTS: Among 174 study patients with typical imaging patterns and protein-truncating PKD1 mutations, 32 (18%) were found to have mild disease on the basis of imaging results (i.e., Mayo Clinic Imaging class 1A-1B), with their mutations spanning the entire gene. By multivariable analyses of age, sex, and mutation class, they displayed mild disease similar to patients with PKD2 mutations and Mayo Clinic Imaging class 1A-1B. Most of these mildly affected patients with protein-truncating PKD1 mutations reported a positive family history of ADPKD in preceding generations and displayed significant intrafamilial disease variability. CONCLUSIONS: Despite having the most severe mutation class, 18% of patients with protein-truncating PKD1 mutations had mild disease on the basis of clinical and imaging assessment. PODCAST: This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2021_02_18_CJN11100720_final.mp3.

Isolated polycystic liver disease genes define effectors of polycystin-1 function.

Dominantly inherited isolated polycystic liver disease (PCLD) consists of liver cysts that are radiologically and pathologically identical to those seen in autosomal dominant polycystic kidney disease, but without clinically relevant kidney cysts. The causative genes are known for fewer than 40% of PCLD index cases. Here, we have used whole exome sequencing in a discovery cohort of 102 unrelated patients who were excluded for mutations in the 2 most common PCLD genes, PRKCSH and SEC63, to identify heterozygous loss-of-function mutations in 3 additional genes, ALG8, GANAB, and SEC61B. Similarly to PRKCSH and SEC63, these genes encode proteins that are integral to the protein biogenesis pathway in the endoplasmic reticulum. We inactivated these candidate genes in cell line models to show that loss of function of each results in defective maturation and trafficking of polycystin-1, the central determinant of cyst pathogenesis. Despite acting in a common pathway, each PCLD gene product demonstrated distinct effects on polycystin-1 biogenesis. We also found enrichment on a genome-wide basis of heterozygous mutations in the autosomal recessive polycystic kidney disease gene PKHD1, indicating that adult PKHD1 carriers can present with clinical PCLD. These findings define genetic and biochemical modulators of polycystin-1 function and provide a more complete definition of the spectrum of dominant human polycystic diseases.

Isolated polycystic liver disease genes define effectors of polycystin-1 function.

Dominantly inherited isolated polycystic liver disease (PCLD) consists of liver cysts that are radiologically and pathologically identical to those seen in autosomal dominant polycystic kidney disease, but without clinically relevant kidney cysts. The causative genes are known for fewer than 40% of PCLD index cases. Here, we have used whole exome sequencing in a discovery cohort of 102 unrelated patients who were excluded for mutations in the 2 most common PCLD genes, PRKCSH and SEC63, to identify heterozygous loss-of-function mutations in 3 additional genes, ALG8, GANAB, and SEC61B. Similarly to PRKCSH and SEC63, these genes encode proteins that are integral to the protein biogenesis pathway in the endoplasmic reticulum. We inactivated these candidate genes in cell line models to show that loss of function of each results in defective maturation and trafficking of polycystin-1, the central determinant of cyst pathogenesis. Despite acting in a common pathway, each PCLD gene product demonstrated distinct effects on polycystin-1 biogenesis. We also found enrichment on a genome-wide basis of heterozygous mutations in the autosomal recessive polycystic kidney disease gene PKHD1, indicating that adult PKHD1 carriers can present with clinical PCLD. These findings define genetic and biochemical modulators of polycystin-1 function and provide a more complete definition of the spectrum of dominant human polycystic diseases.

Evaluation of Reference Genes for RT-qPCR Studies in the Seagrass Zostera muelleri Exposed to Light Limitation.

Seagrass meadows are threatened by coastal development and global change. In the face of these pressures, molecular techniques such as reverse transcription quantitative real-time PCR (RT-qPCR) have great potential to improve management of these ecosystems by allowing early detection of chronic stress. In RT-qPCR, the expression levels of target genes are estimated on the basis of reference genes, in order to control for RNA variations. Although determination of suitable reference genes is critical for RT-qPCR studies, reports on the evaluation of reference genes are still absent for the major Australian species Zostera muelleri subsp. capricorni (Z. muelleri). Here, we used three different software (geNorm, NormFinder and Bestkeeper) to evaluate ten widely used reference genes according to their expression stability in Z. muelleri exposed to light limitation. We then combined results from different software and used a consensus rank of four best reference genes to validate regulation in Photosystem I reaction center subunit IV B and Heat Stress Transcription factor A- gene expression in Z. muelleri under light limitation. This study provides the first comprehensive list of reference genes in Z. muelleri and demonstrates RT-qPCR as an effective tool to identify early responses to light limitation in seagrass.

The cleaved cytoplasmic tail of polycystin-1 regulates Src-dependent STAT3 activation.

Polycystin-1 (PC1) mutations result in proliferative renal cyst growth and progression to renal failure in autosomal dominant polycystic kidney disease (ADPKD). The transcription factor STAT3 (signal transducer and activator of transcription 3) was shown to be activated in cyst-lining cells in ADPKD and PKD mouse models and may drive renal cyst growth, but the mechanisms leading to persistent STAT3 activation are unknown. A proteolytic fragment of PC1 corresponding to the cytoplasmic tail, PC1-p30, is overexpressed in ADPKD. Here, we show that PC1-p30 interacts with the nonreceptor tyrosine kinase Src, resulting in Src-dependent activation of STAT3 by tyrosine phosphorylation. The PC1-p30-mediated activation of Src/STAT3 was independent of JAK family kinases and insensitive to the STAT3 inhibitor suppressor of cytokine signaling 3. Signaling by the EGF receptor (EGFR) or cAMP amplified the activation of Src/STAT3 by PC1-p30. Expression of PC1-p30 changed the cellular response to cAMP signaling. In the absence of PC1-p30, cAMP dampened EGFR- or IL-6-dependent activation of STAT3; in the presence of PC1-p30, cAMP amplified Src-dependent activation of STAT3. In the polycystic kidney (PCK) rat model, activation of STAT3 in renal cystic cells depended on vasopressin receptor 2 (V2R) signaling, which increased cAMP levels. Genetic inhibition of vasopressin expression or treatment with a pharmacologic V2R inhibitor strongly suppressed STAT3 activation and reduced renal cyst growth. These results suggest that PC1, via its cleaved cytoplasmic tail, integrates signaling inputs from EGFR and cAMP, resulting in Src-dependent activation of STAT3 and a proliferative response.

Insula and orbitofrontal cortical morphology in substance dependence is modulated by sex.

BACKGROUND AND PURPOSE: Frontolimbic circuits are involved in learning and decision-making processes thought to be affected in substance-dependent individuals. We investigated frontolimbic cortical morphometry in substance-dependent men and women and determined whether morphometric measurements correlated with decision-making performance. MATERIALS AND METHODS: Twenty-eight abstinent SDI (17 men/11 women) were compared with 28 controls (13 men/15 women). Cortical thicknesses and volumes were computed by using FreeSurfer. After controlling for age and intracranial volume, group and sex effects were analyzed in 3 a priori regions of interest: the insula, orbitofrontal cortex, and anterior cingulate cortex by using analysis of covariance. A secondary whole-brain analysis was conducted to verify region-of-interest results and to explore potential differences in other brain regions. RESULTS: Region-of-interest analyses revealed a main effect of group on the left insula cortex, which was thinner in SDI compared with controls (P = .02). There was a group by sex interaction on bilateral insula volume (left, P = .02; right, P = .001) and right insula cortical thickness (P = .007). Compared with same-sex controls, female SDI had smaller insulae, whereas male SDI had larger insulae. Neither ACC nor OFC significantly differed across group. Performance on a decision-making task was better in controls than SDI and correlated with OFC measurements in the controls. CONCLUSIONS: SDI and controls differed in insula morphology, and those differences were modulated by sex. No group differences in OFC were observed, but OFC measurements correlated with negative-reinforcement learning in controls. These preliminary results are consistent with a hypothesis that frontolimbic pathways may be involved in behaviors related to substance dependence.

Modelling formulations using gene expression programming--a comparative analysis with artificial neural networks.

This study has investigated the utility and potential advantages of gene expression programming (GEP)--a new development in evolutionary computing for modelling data and automatically generating equations that describe the cause-and-effect relationships in a system--to four types of pharmaceutical formulation and compared the models with those generated by neural networks, a technique now widely used in the formulation development. Both methods were capable of discovering subtle and non-linear relationships within the data, with no requirement from the user to specify the functional forms that should be used. Although the neural networks rapidly developed models with higher values for the ANOVA R(2) these were black box and provided little insight into the key relationships. However, GEP, although significantly slower at developing models, generated relatively simple equations describing the relationships that could be interpreted directly. The results indicate that GEP can be considered an effective and efficient modelling technique for formulation data.

Effect of crystallisation conditions and feedstock morphology on the aerosolization performance of micronised salbutamol sulphate.

Salbutamol sulphate (SS) used in dry powder inhalers requires drug particles in the respirable size range of 1-5 µm to achieve a suitable therapeutic effect. The aim of this study was therefore to determine strategies for controlling drug substance characteristics pre and post-crystallisation to facilitate the production of micronised SS with desirable particle attributes for optimal delivery as an inhaled aerosol. SS batches were crystallised using an antisolvent method to produce a range of crystal morphologies. Air jet milling was then used to reduce the size of crystallised SS particles. Starting materials and micronised batches of SS were characterised in the solid state using a range of techniques with subsequent assessment of aerosol properties. Assessment of the aerodynamic characteristics of micronised SS delivered by DPI (without any carrier) indicated that fine particle fraction and emitted dose as a percentage of the total recovered dose were dependent on the quality attributes of the micronised SS, which were directly linked to the degree of imperfections and the morphology of the crystalline feedstock used in micronisation. Aerosolization performance of micronised SS can be optimised by manipulation of feedstock characteristics through crystal engineering and through definition of optimal processing conditions for micronisation.

Comminution of ibuprofen to produce nano-particles for rapid dissolution.

A critical problem associated with poorly soluble drugs is low and variable bioavailability derived from slow dissolution and erratic absorption. The preparation of nano-formulations has been identified as an approach to enhance the rate and extent of drug absorption for compounds demonstrating limited aqueous solubility. A new technology for the production of nano-particles using high speed, high efficiency processes that can rapidly generate nano-particles with rapid dissolution rate has been developed. Size reduction of a low melting ductile model compound was achieved in periods less than 1h. Particle size reduction of ibuprofen using this methodology resulted in production of crystalline particles with average diameter of approximately 270nm. Physical stability studies showed that the nano-suspension remained homogeneous with slight increases in mean particle size, when stored at room temperature and under refrigerated storage conditions 2-8°C for up to 2 days. Powder containing crystalline drug was prepared by spray-drying ibuprofen nano-suspensions with mannitol dissolved in the aqueous phase. Dissolution studies showed similar release rates for the nano-suspension and powder which were markedly improved compared to a commercially available drug product. Ibuprofen nano-particles could be produced rapidly with smaller sizes achieved at higher suspension concentrations. Particles produced in water with stabilisers demonstrated greatest physical stability, whilst rapid dissolution was observed for the nano-particles isolated in powder form.

The impact of material attributes and process parameters on the micronisation of lactose monohydrate.

Dry powder inhalers (DPIs), which are important medicines for drug delivery to the lungs, require drug particles in the respirable size range of 1-6 µm for optimal lung deposition. Drugs administered by the oral route also derive benefit from particles in this size range owing to their large surface area to volume ratio, which provides potential for rapid dissolution. Micronisation used in the production of particles, however often leads to heterogeneous product containing mechanically activated surfaces with amorphous content. This study was therefore carried out to evaluate the effect of particle properties of three grades of lactose monohydrate, with sizes above and below the brittle-ductile transition (dcrit) and their interaction with process variables on the quality of micronised material. Following an experimental design, the impact of three factors (grinding pressure, injector pressure and feed rate) on the particulate attributes of micronised powders produced from the different size grades was assessed. Processing conditions were shown to be important determinants of powder properties only for the coarsest starting material. Ultrafine material was achieved by processing finer grade feed stock below dcrit. However the resultant product was more crystalline and transformed on heating to the anhydrous state with markedly reduced onset temperature with lower energy surfaces than powders produced from larger sized starting material. Thus the propensity for micronisation of lactose monohydrate can be altered through control of starting materials and optimal settings for process variables.

A combined modelling and experimental study of the surface energetics of alpha-lactose monohydrate.

The surface energy of alpha-lactose monohydrate measured by inverse gas chromatography (IGC) is reported along with a dynamic molecular modelling study of the interaction of the various molecular probes with different surfaces of alpha-lactose monohydrate. The IGC results show that alpha-lactose monohydrate is acidic in nature. Using quantitative calculations of the energy of adsorption, the acidic nature of the surface is confirmed and the calculated values agree closely with the experimentally measured values. Along with the acidic nature, dynamic molecular modelling also reveals that the presence of a channel and water molecules on a surface affects the surface energetics of that face. The presence of water on the surface can decrease or increase the surface energy by either blocking or attracting a probe molecule, respectively. This property of water depends on its position and association with other functional groups present on the surface. The effect of a channel or cavity on the surface energy is shown to depend on its size, which determines whether the functional groups in the channel are assessable by probe molecules or not. Overall molecular modelling explains, at the molecular level, the effect of different factors affecting the surface energy of individual faces of the crystal.

Design of a fixed-dose paediatric combination of artesunate and amodiaquine hydrochloride.

Fixed-dose combinations of artesunate and amodiaquine hydrochloride provide challenges in product development due to the incompatibility of the two agents. This is particularly critical for paediatric preparations which can often be presented in liquid form. The studies reported in this article aimed to develop an understanding of the factors responsible for this incompatibility, whilst assessing the feasibility of developing a stable paediatric formulation. The stability characteristics of fast-disintegrating granular formulations containing intimate mixtures of both agents and single agent granules blended prior to production of unit doses were therefore studied under a range of storage conditions. The granular products remained stable over the 3-month period under stressed accelerated conditions, in contrast to control samples containing both drugs in combined granular form, which demonstrated reductions in artesunate content at elevated humidity. It was hypothesized that loss of active agent content for artesunate was accelerated by access to the water of crystallization of amodiaquine as demonstrated by the more facile dehydration of amodiaquine when a mixture of the two agents was analysed by differential scanning calorimetry (DSC). It was therefore concluded that a stable, versatile paediatric preparation of the two drugs could be prepared by blending pre-formulated granules containing the individual constituents rather than producing a combined granule comprising intimate mixtures of the two agents.

Advantages of neurofuzzy logic against conventional experimental design and statistical analysis in studying and developing direct compression formulations.

This study has investigated the utility and potential advantages of an artificial intelligence technology - neurofuzzy logic - as a modeling tool to study direct compression formulations. The modeling performance was compare with traditional statistical analysis. From results it can be stated that the normalized error obtained from neurofuzzy logic was lower. Compared to the multiple regression analysis neurofuzzy logic showed higher accuracy in prediction for the five outputs studied. Rule sets generated by neurofuzzy logic are completely in agreement with the findings based on statistical analysis and advantageously generate understandable and reusable knowledge. Neurofuzzy logic is easy and rapid to apply and outcomes provided knowledge not revealed via statistical analysis.

Separation processes for organic molecules using SCF Technologies.

Supercritical fluids have been applied for many years for the separation of solutes from solids or solute mixtures in both exploratory and industrial applications. In the pharmaceutical industry the generation of pure solid states without impurities is important as the presence of impurities can result in a change in chemical properties or lead to physical instability. The literature on the separation and purification of solutes from solid matrices and solute mixtures using supercritical fluids, with the main emphasis on pharmaceutically important molecules, is reviewed in this article. Also discussed is the application of supercritical fluids in the control of process impurities such as chemical intermediates and residual solvent and in polymorphic control and chiral resolution. As the generation of organic molecules of pharmaceutical interest with high purity is important in pharmaceuticals this review additionally provides a brief overview of highly selective chemical reactions in supercritical fluids.

Data mining of fractured experimental data using neurofuzzy logic-discovering and integrating knowledge hidden in multiple formulation databases for a fluid-bed granulation process.

In the pharmaceutical field, current practice in gaining process understanding by data analysis or knowledge discovery has generally focused on dealing with single experimental databases. This limits the level of knowledge extracted in the situation where data from a number of sources, so called fractured data, contain interrelated information. This situation is particularly relevant for complex processes involving a number of operating variables, such as a fluid-bed granulation. This study investigated three data mining strategies to discover and integrate knowledge "hidden" in a number of small experimental databases for a fluid-bed granulation process using neurofuzzy logic technology. Results showed that more comprehensive domain knowledge was discovered from multiple databases via an appropriate data mining strategy. This study also demonstrated that the textual information excluded in individual databases was a critical parameter and often acted as the precondition for integrating knowledge extracted from different databases. Consequently generic knowledge of the domain was discovered, leading to an improved understanding of the granulation process.

Crystal engineering of active pharmaceutical ingredients to improve solubility and dissolution rates.

The increasing prevalence of poorly soluble drugs in development provides notable risk of new products demonstrating low and erratic bioavailability with consequences for safety and efficacy, particularly for drugs delivered by the oral route of administration. Although numerous strategies exist for enhancing the bioavailability of drugs with low aqueous solubility, the success of these approaches is not yet able to be guaranteed and is greatly dependent on the physical and chemical nature of the molecules being developed. Crystal engineering offers a number of routes to improved solubility and dissolution rate, which can be adopted through an in-depth knowledge of crystallisation processes and the molecular properties of active pharmaceutical ingredients. This article covers the concept and theory of crystal engineering and discusses the potential benefits, disadvantages and methods of preparation of co-crystals, metastable polymorphs, high-energy amorphous forms and ultrafine particles. Also considered within this review is the influence of crystallisation conditions on crystal habit and particle morphology with potential implications for dissolution and oral absorption.

Investigation of an artificial intelligence technology--Model trees. Novel applications for an immediate release tablet formulation database.

This study has investigated an artificial intelligence technology - model trees - as a modelling tool applied to an immediate release tablet formulation database. The modelling performance was compared with artificial neural networks that have been well established and widely applied in the pharmaceutical product formulation fields. The predictability of generated models was validated on unseen data and judged by correlation coefficient R(2). Output from the model tree analyses produced multivariate linear equations which predicted tablet tensile strength, disintegration time, and drug dissolution profiles of similar quality to neural network models. However, additional and valuable knowledge hidden in the formulation database was extracted from these equations. It is concluded that, as a transparent technology, model trees are useful tools to formulators.