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The cultivation of meadow orchards provides an ecological benefit for biodiversity, which is significantly higher than in intensively cultivated orchards. However, the maintenance of meadow orchards is not economically profitable. The use of automation for pruning would reduce labour costs and avoid accidents. The goal of this research was, using photogrammetric point clouds, to automatically calculate tree models, without additional human input, as basis to estimate pruning points for meadow orchard trees. Pruning estimates require a knowledge of the major tree structure, containing the branch position, the growth direction and their topological connection. Therefore, nine apple trees were captured photogrammetrically as 3D point clouds using an RGB camera. To extract the tree models, the point clouds got filtered with a random forest algorithm, the trunk was extracted and the resulting point clouds were divided into numerous K-means clusters. The cluster centres were used to create skeleton models using methods of graph theory. For evaluation, the nodes and edges of the calculated and the manually created reference tree models were compared. The calculated models achieved a producer’s accuracy of 73.67% and a user's accuracy of 74.30% of the compared edges. These models now contain the geometric and topological structure of the trees and an assignment of their point clouds, from which further information, such as branch thickness, can be derived on a branch-specific basis. This is necessary information for the calculation of pruning areas and for the actual pruning planning, needed for the automation of tree pruning.

Farmers are facing severe problems with weed competition in cereal crops. Grass-weeds and perennial weed species became more abundant in Europe mainly due to high percentages of cereal crops in cropping systems and reduced tillage practices combined with continuous applications of herbicides with the same mode of action. Several weed populations have evolved resistance to herbicides. Precision weed hoeing may help to overcome these problems. So far, weed hoeing in cereals was restricted to cropping practices with row distances of more than 200 mm. Hoeing in cereals with conventional row distances of 125–170 mm requires the development of automatic steering systems. The objective of this project was to develop a new automatic guidance system for inter-row hoeing using camera-based row detection and automatic side-shift control. Six field studies were conducted in winter wheat to investigate accuracy, weed control efficacy and crop yields of this new hoeing technology. A three-meter prototype and a 6-meter segmented hoe were built and tested at three different speeds in 150 mm seeded winter wheat. The maximum lateral offset from the row center was 22.53 mm for the 3 m wide hoe and 18.42 mm for the 6 m wide hoe. Camera-guided hoeing resulted in 72–96% inter-row and 21–91% intra-row weed control efficacy (WCE). Weed control was 7–15% higher at 8 km h−1 compared to 4 km h−1. WCE could be increased by 14–22% when hoeing was combined with weed harrowing. Grain yields after camera-guided hoeing at 8 km h−1 were 15–76% higher than the untreated control plots and amounted the same level as the weed-free herbicide plots. The study characterizes camera-guided hoeing in cereals as a robust and effective method of weed control.

BackgroundOver the past years, several emergency medical service providers have introduced mechanical chest compression devices (MCDs) in their protocols for cardiopulmonary resuscitation (CPR). Especially in helicopter emergency medical systems (HEMS), which have limitations regarding loading weight and space and typically operate in rural and remote areas, whether MCDs have benefits for patients is still unknown. The aim of this study was to evaluate the use of MCDs in a large Swiss HEMS system.Materials and methodsWe conducted a retrospective observational study of all HEMS missions of Swiss Air rescue Rega between January 2014 and June 2016 with the use of an MCD (Autopulse®). Details of MCD use and patient outcome are reported from the medical operation journals and the hospitals’ discharge letters.ResultsMCDs were used in 626 HEMS missions, and 590 patients (94%) could be included. 478 (81%) were primary missions and 112 (19%) were interhospital transfers. Forty-nine of the patients in primary missions were loaded under ongoing CPR with MCDs. Of the patients loaded after return of spontaneous circulation (ROSC), 20 (7%) experienced a second CA during the flight. In interhospital transfers, 102 (91%) only needed standby use of the MCD. Five (5%) patients were loaded into the helicopter with ongoing CPR. Five (5%) patients went into CA during flight and the MCD had to be activated. A shockable cardiac arrhythmia was the only factor significantly associated with better survival in resuscitation missions using MCD (OR 0.176, 95% confidence interval 0.084 to 0.372,p ConclusionWe conclude that equipping HEMS with MCDs may be beneficial, with non-trauma patients potentially benefitting more than trauma patients.

Three dimensional (3-D) reconstruction of maize plant morphology by proximal sensing in agriculture brings high definition data that can be used for a number of applications related with precision agriculture and agricultural robotics. However, 3-D reconstruction without methodologies for extracting useful information is a senseless strategy. In this research, a methodology for stem position estimation is presented relying on the merging of four point clouds, using the Iterative Closes Point algorithm, that were generated from different 3-D perspective views. The proposed methodology is based on bivariate point density histograms for detecting the regional maxima and a radius filter based on the closest Euclidean distance. Then, single plant segmentation was performed by projecting a spatial cylindrical boundary around the estimated stem positions on a merged plant and soil point cloud. After performing a local Random Sample Consensus, the segmented plant point cloud was clustered using the Density-based spatial clustering of applications with noise algorithm. Additionally, a height profile was generated by rasterizing the plant and soil point clouds, separately, with different cell widths. The rasterized soil point cloud was meshed, and the rasterized plant points to soil mesh distance was calculated. The resulting plant stem positions were estimated with an average mean error and standard deviation of 24 mm and 14 mm, respectively. Equivalently, the average mean error and standard deviation of the individual plant height estimation was 30 mm and 35 mm, respectively. Finally, the overall plant height profile mean error average was 8.7 mm. Thus it is possible to determine the stem position and plant height of reconstructed maize plants using a low-cost time-of-flight camera.

A two dimensional (2D) laser scanner was mounted at the front part of a small 4-wheel autonomous robot with differential steering, at an angle of 30 ° pointing downwards. The machine was able to drive between maize rows and collect concurrent time-stamped data. A robotic total station tracked the position of a prism mounted on the vehicle. The total station and laser scanner data were fused to generate a three dimensional (3D) point cloud. This 3D representation was used to detect individual plant positions, which are of particular interest for applications such as phenotyping, individual plant treatment and precision weeding. Two different methodologies were applied to the 3D point cloud to estimate the position of the individual plants. The first methodology used the Euclidian Clustering on the entire point cloud. The second methodology utilised the position of an initial plant and the fixed plant spacing to search iteratively for the best clusters. The two algorithms were applied at three different plant growth stages. For the first method, results indicated a detection rate up to 73.7% with a root mean square error of 3.6 cm. The second method was able to detect all plants (100% detection rate) with an accuracy of 2.7–3.0 cm, taking the plant spacing of 13 cm into account.

A current problem in the design of small and lightweight autonomous agricultural robots is how to create sufficient traction on soil to pull an agricultural implement or load. One promising solution is offered by the interlock drive system, which penetrates spikes into the soil to create traction. The combination of soil penetrating spikes and a push-pull design offers new possibilities for vehicle control. By controlling the interlocking of the spikes and pushing and pulling them against the main frame, the vehicle can perform tight maneuvers. To validate this idea, we designed a robot, capable of creating high traction and performing headland turns. The navigation of the new robot system is performed by actively pushing the spikes, mounted on a slide into the soil, while the main frame is pushed back and pulled forward. The vehicle of 2-meter length was able to turn on the spot, and could follow a straight line, just using the spikes and the push-pull mechanism. The trajectory and the performed measurements suggest, that a vehicle which uses only spikes for traction and steering is fully capable of performing autonomous tasks in agriculture fields.

Point cloud rigid registration and stitching for plants with complex architecture is a challenging task, however, it is an important process to take advantage of the full potential of 3-D cameras for plant phenotyping and agricultural automation for characterizing production environments in agriculture. A methodology for three-dimensional (3-D) reconstruction of maize crop rows was proposed in this research, using high resolution 3-D images that were mapped into the colour images using state-of-the art software. The point cloud registration methodology was based on the Iterative Closest Point (ICP) algorithm. The incoming point cloud was previously filtered using the Random Sample Consensus (RANSAC) algorithm, by reducing the number of soil points until a threshold value was reached. This threshold value was calculated based on the approximate number of plant points in a single 3-D image. After registration and stitching of the crop rows, a plant/soil segmentation process was done relying again on the RANSAC algorithm. A quantitative comparison showed that the number of points obtained with a time-of-flight (TOF) camera, compared with the ones from two light detection and ranging (LIDARs) from a previous research, was roughly 23 times larger. Finally, the reconstruction was validated by comparing the seedling positions as ground truth and the point cloud clusters, obtained using the k-means clustering, that represent the plant stem positions. The resulted maize positions from the proposed methodology closely agreed with the ground truth with an average mean and standard deviation of 3.4 cm and ±1.3 cm, respectively.

The search for approaches to a holistic sustainable agriculture requires the development of new cropping systems that provide additional ecosystem services beyond biomass supply for food, feed, material, and energy use. The reduction of chemical synthetic plant protection products is a key instrument to protect vulnerable natural resources such as groundwater and biodiversity. Together with an optimal use of mineral fertilizer, agroecological practices, and precision agriculture technologies, a complete elimination of chemical synthetic plant protection in mineral-ecological cropping systems (MECSs) may not only improve the environmental performance of agroecosystems, but also ensure their yield performance. Therefore, the development of MECSs aims to improve the overall ecosystem services of agricultural landscapes by (i) improving the provision of regulating ecosystem services compared to conventional cropping systems and (ii) improving the supply of provisioning ecosystem services compared to organic cropping systems. In the present review, all relevant research levels and aspects of this new farming concept are outlined and discussed based on a comprehensive literature review and the ongoing research project “Agriculture 4.0 without Chemical-Synthetic Plant Protection”.

To overcome the limited transmission range of spatially separated nodes of a wireless sensor network (WSN), a small 4-wheel autonomous robot assembled the data from nodes distributed in a vineyard. First, the robot followed a predefined way-point route between the grapevine rows, in order to evaluate the sensor node locations by their received signal strength indication (RSSI). Then, the recorded and geo-referenced RSSI data were analysed and mapped. By using the evaluated node positions, an optimised second route was generated. While navigating, a laser scanner was used for obstacle detection and avoidance. Path planning with known positions of the nodes reduced the driving time by 15 times compared with the first run, because the hybrid control system used was capable of navigating within the plantation even perpendicular to the row structures. For locating the nodes, results based on trilateration were compared with the values of an attached differential global navigation satellite system (DGNSS). The results showed that it is possible to locate and geo-reference the sensor nodes with a robot, even without any prior knowledge about their absolute position. The best achieved location showed a deviation with DGNSS of 1.2 m and with RSSI trilateration of 0.6 m compared to the actual position.

Plant/background segmentation is a key component of digital image analysis in agriculture. It can be used for yield prediction models, crop growth, disease diagnosis and automated navigation tasks. In particular, well-known segmentation methods are strongly influenced by changing light conditions during image acquisition as well as different color variations of plants and the background in the scene. In this work, an algorithm was developed and evaluated which can perform robust automated plant/background segmentation under varying capture conditions such as overexposure or underexposure along with diverse colors of the crop and background. The algorithm relies on an index-based method for approximate pre-segmentation and uses this first approximation to calculate the threshold value for a segmentation using a color space model. The performance of the algorithm was evaluated with 200 images from 4 different cameras and settings. Furthermore, the algorithm quality was compared with existing index-based segmentation methods such as the excess green index, the excess red index, excess green minus excess red index. All indices were combined with Otsu thresholding. The results showed that the novel approach has a more robust performance and is more reliable than the other index-based segmentation methods. The investigations showed excellent results of the algorithm using the CieLab color space with semantic plant segmentation accuracies of 97.4%.

The leaf area is an important plant parameter for plant status and crop yield. In this paper, a low-cost time-of-flight camera, the Kinect v2, was mounted on a robotic platform to acquire 3-D data of maize plants in a greenhouse. The robotic platform drove through the maize rows and acquired 3-D images that were later registered and stitched. Three different maize row reconstruction approaches were compared: reconstruct a crop row by merging point clouds generated from both sides of the row in both directions, merging point clouds scanned just from one side, and merging point clouds scanned from opposite directions of the row. The resulted point cloud was subsampled and rasterized, the normals were computed and re-oriented with a Fast Marching algorithm. The Poisson surface reconstruction was applied to the point cloud, and new vertices and faces generated by the algorithm were removed. The results showed that the approach of aligning and merging four point clouds per row and two point clouds scanned from the same side generated very similar average mean absolute percentage error of 8.8% and 7.8%, respectively. The worst error resulted from the two point clouds scanned from both sides in opposite directions with 32.3%.

The goal of this work was to cluster maize plants perception points under six different growth stages in noisy 3D point clouds with known positions. The 3D point clouds were assembled with a 2D laser scanner mounted at the front of a mobile robot, fusing the data with the precise robot position, gained by a total station and an Inertial Measurement Unit. For clustering the single plants in the resulting point cloud, a graph-cut based algorithm was used. The algorithm results were compared with the corresponding measured values of plant height and stem position. An accuracy for the estimated height of 1.55 cm and the stem position of 2.05 cm was achieved.

Intra-row weeding is a time consuming and challenging task. Therefore, a rotary weeder implement for an autonomous electrical robot was developed. It can be used to remove the weeds of the intra-row area of orchards and vineyards. The hydraulic motor of the conventional tool was replaced by an electric motor and some mechanical parts were refabricated to reduce the overall weight. The side shift, the height and the tilt adjustment were performed by linear electric motors. For detecting the trunk positions, two different methods were evaluated: A conventional electromechanical sensor (feeler) and a sonar sensor. The robot performed autonomous row following based on two dimensional laser scanner data. The robot prototype was evaluated at a forward speed of 0.16 ms&minus, 1 and a working depth of 40 mm. The overall performance of the two different trunk detection methods was tested and evaluated for quality and power consumption. The results indicated that an automated intra-row weeding robot could be an alternative solution to actual machinery. The overall performance of the sonar was better than the adjusted feeler in the performed tests. The combination of autonomous navigation and weeding could increase the weeding quality and decrease power consumption in future.

To develop robust algorithms for agricultural navigation, different growth stages of the plants have to be considered. For fast validation and repeatable testing of algorithms, a dataset was recorded by a 4 wheeled robot, equipped with a frame of different sensors and was guided through maize rows. The robot position was simultaneously tracked by a total station, to get precise reference of the sensor data. The plant position and parameters were measured for comparing the sensor values. A horizontal laser scanner and corresponding total station data was recorded for 7 times over a period of 6 weeks. It was used to check the performance of a common RANSAC row algorithm. Results showed the best heading detection at a mean growth height of 0.268 m.

Abstract 1952 Background: Initial clinical response rates have improved significantly with current treatments for multiple myeloma (MM). However, most patients eventually relapse or become refractory to approved agents, prompting the development of additional targeted agents and combination regimens. Vorinostat is a first-in-class oral histone deacetylase inhibitor that regulates the expression of genes and proteins involved in tumor growth and survival, and is approved in the United States for the treatment of patients with advanced cutaneous T-cell lymphoma in whom prior therapies have failed. Bortezomib, a reversible proteasome inhibitor, is approved for the treatment of patients with MM who have received at least 1 prior therapy. The synergistic effects of vorinostat and bortezomib have been shown in preclinical studies and confirmed in Phase I trials in patients with relapsed/refractory (RR) MM, producing objective response rates (ORRs; partial response or better) of up to 42% in all patients (including those with bortezomib-refractory disease) and overall clinical benefit of up to 90%. Methods: Vantage 088 is a global, Phase III, randomized, double-blind study to investigate the safety and efficacy of vorinostat vs placebo in combination with bortezomib in patients with relapsed MM and progressive disease after 1–3 prior antimyeloma regimens. The primary objective is to determine the duration of progression-free survival, with a planned enrollment of 742 patients. Overall survival, time to progression, ORR, tolerability, and patient-reported outcomes (PROs) will be included as secondary and exploratory outcomes. A distinctive aspect of this study design involves the evaluation of PROs using validated instruments, including quality-of-life (QoL) questionnaires for cancer patients (EORTC QLQ-C30) and myeloma patients (EORTC QLQ-MY20) and the EuroQoL-5D, presenting an opportunity to correlate PROs with efficacy and safety data. Interim analysis will take place when at least 126 events have occurred. Vantage 095 is a Phase IIB open-label study to investigate the efficacy and tolerability of vorinostat combined with bortezomib in patients with RR MM who had received ≥2 prior antimyeloma regimens; were refractory to bortezomib; and were relapsed, refractory to, intolerant of, or ineligible for other MM therapies, including immunomodulatory drugs (IMiDs). The primary objective is to determine the ORR, with a planned enrollment of 142 patients. In both studies, patients receive 21-day cycles of intravenous bortezomib (1.3 mg/m2; days 1, 4, 8, and 11) combined with oral vorinostat 400 mg (or matching placebo in Vantage 088) once daily on days 1–14. Efficacy is assessed using European Bone and Marrow Transplantation Group criteria. Adverse events (AEs; including clinical and laboratory events) are assessed and recorded using the National Cancer Institute Common Terminology Criteria for Adverse Events (version 3.0). Results: Vantage 088: As of June 11, 2010, 349 patients (range, 1–17 cycles) were randomized. Patients received a median of 2 prior regimens (range, 1–3 regimens; 25% prior bortezomib, 48% prior thalidomide, and 12% prior lenalidomide). Vantage 095: As of June 11, 2010, 108 patients were enrolled. Patients (median age, 62 y; 57% men; 67% with Eastern Cooperative Oncology Group performance status 1) were heavily pretreated (median prior regimens, 5 [range, 2–17]). Interim efficacy data were reviewed in January 2010 by an independent data monitoring committee (DMC) for the first 43 patients enrolled; the futility threshold was passed, and final results are expected to be available 2Q2011. Conclusion: 2 ongoing global, multicenter, investigational trials are evaluating the efficacy and safety of combined vorinostat and bortezomib in patients with RR MM and are rapidly accruing patients. The Vantage 088 trial has passed the initial safety evaluations by the DMC, while interim results from Vantage 095 suggest that combined vorinostat and bortezomib may have clinical activity in patients with RR MM who are refractory to bortezomib and IMiDs and ineligible for other regimens. Disclosures: Siegel: Celgene and Millennium: Advisory Board, Speakers Bureau; Merck: Advisory Board, Consultancy. Off Label Use: Vorinostat Combined with Bortezomib for treatment in Multiple Myeloma. Jagannath:Celgene: Honoraria; Millenium: Honoraria; Ortho Biotech: Honoraria; Onyx Pharma: Honoraria; Merck: Honoraria; Proteolix: Honoraria; Imedex: Speakers Bureau; Medicom World Wide: Speakers Bureau; Optum Health Education: Speakers Bureau; PER Group: Speakers Bureau. Hajek:Janssen-Cilag: Honoraria; Celgene: Honoraria; Merck, Sharp, and Dohme: Honoraria. Dimopoulos:MSD: Honoraria, Membership on an entity's Board of Directors or advisory committees; Millenium: Honoraria, Membership on an entity's Board of Directors or advisory committees; Ortho Biotech: Honoraria, Membership on an entity's Board of Directors or advisory committees. Lonial:Millennium: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Onyx: Consultancy, Research Funding. Graef:Merck Research Laboratories: Employment. Pietrangelo:Merck Research Laboratories: Employment. Lupinacci:Merck Research Laboratories: Employment. Reiser:Merck Research Laboratories: Employment. Anderson:Millennium Pharmaceuticals: Consultancy; Celgene: Consultancy; Novartis: Consultancy; Onyx: Consultancy; Merck: Consultancy; BMS: Consultancy; Acetylon: Equity Ownership, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau.

Abstract 3890 Poster Board III-826 Introduction Multiple myeloma (MM) is characterized by the accumulation of malignant plasma cells in the bone marrow. MM accounts for approximately 1% of all new cancer diagnoses and is the second most common hematologic malignancy in adults. Despite recent advances in therapy, MM remains largely incurable and there is a need to develop new treatments or treatment regimens to combat MM. Vorinostat is an oral histone deacetylase (HDAC) inhibitor approved for the treatment of cutaneous manifestations of T-cell lymphoma in patients with progressive, persistent, or recurrent disease on or following two systemic therapies. As HDACs are over-expressed and involved in the regulation of transcription with recruitment by oncogenic transcription factors in a variety of tumor types, the efficacy of vorinostat is currently under investigation in a number of hematologic and solid malignancies, including MM. Bortezomib is a proteasome inhibitor that has provided significant survival advantages for patients with MM. Preclinical studies have shown that the combination of vorinostat and bortezomib synergistically induces MM cell apoptosis. Results from two Phase I studies showed that the combination of vorinostat and bortezomib (+/- dexamethasone) is well tolerated and achieves ∼ 40% objective response rate in a relapsed/refractory MM population, even in those patients who were refractory to prior bortezomib treatment (Weber et al. Clinical Lymphoma and Myeloma 2009;9:S44, abstract A248) (Weber et al. Clinical Lymphoma and Myeloma 2009; 9:S42, abstract A242). Encouraging results observed in these trials led to the design of a Phase IIb, international, multicenter, open-label study that will assess the efficacy and tolerability of vorinostat in combination with bortezomib in advanced MM patients. Methods Patients (aged ≥18 years) with relapsed and refractory MM after two prior treatment regimens, including at least one bortezomib-containing regimen, and who are relapsed, refractory, intolerant, or ineligible for other therapies, including immunomodulatory agents, were included in this trial. Patients received intravenous bortezomib 1.3 mg/m2 on Days 1, 4, 8, and 11 and oral vorinostat 400 mg once daily on Days 1-14 of each 21-day cycle. The addition of oral dexamethasone (20 mg on the day of and day after each bortezomib dose) was permitted for patients who experienced disease progression after two treatment cycles or no change (stable disease) after four cycles, until further disease progression. The primary endpoint is objective response rate and secondary endpoints include assessment of: safety, time to disease progression, progression-free survival, and overall survival. Patient-reported outcomes were collected in this study as an exploratory objective. Study enrollment At the time of submission, 38 patients (out of 142) have been enrolled in the trial. A first interim futility analysis is planned after the 43rd patient has been enrolled. At the time of the meeting, safety data, along with enrollment status and timelines for future data read-outs, will be reported. Disclosures: Siegel: Celegne: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Millennium: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Off Label Use: Vorinostat is a histone deacetylase (HDAC) inhibitor that was approved in the FDA in October 2006 for the treatment of cutaneous manifestations in patients with cutaneous T-cell lymphoma (CTCL) who have progressive, persistent, or recurrent disease on or following two systemic therapies. Jagannath:Millennium: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria; Merck: Honoraria. Lonial:Celgene: Consultancy; Millennium: Consultancy, Research Funding; BMS: Consultancy; Novartis: Consultancy; Gloucester: Research Funding. Dimopoulos:MSD: Honoraria; Celgene: Honoraria. Graef:Merck: Employment, Equity Ownership. Pietrangelo:Merck: Employment, Equity Ownership. Lupinacci:Merck: Employment, Equity Ownership. Reiser:Merck: Employment, Equity Ownership. Rizvi:Merck: Employment. Anderson:Millennium: Consultancy, Honoraria, Speakers Bureau; Celgene: Consultancy, Honoraria, Speakers Bureau; Novartis: Consultancy, Honoraria, Research Funding.

Abstract 3886 Poster Board III-822 Introduction A better understanding of multiple myeloma (MM) disease biology has led to the development of targeted agents such as the proteasome inhibitor bortezomib. While bortezomib has provided significant survival advantages for both previously untreated and treated patients with MM, nearly all patients eventually relapse or become refractory to bortezomib therapy. Therefore, there remains a need to develop specific new approaches that are active against MM or enhance the efficacy of existing treatments. Vorinostat (Zolinza®), a potent oral inhibitor of Class I and Class II histone deacetylase (HDAC) enzymes, has demonstrated antiproliferative and proapoptotic activity in preclinical models of MM as a single agent and in combination with bortezomib. Preliminary results from an ongoing open-label, escalating dose, multicenter Phase I trial of vorinostat in combination with bortezomib have shown that the combination is generally well tolerated and effective in heavily pretreated patients with advanced MM (Weber et al. Clinical Lymphoma and Myeloma 2009; 9: S44, abstract A248), including patients refractory to prior bortezomib treatment (Weber et al. Clinical Lymphoma and Myeloma 2009; 9: S42, abstract A242). Here we report the safety and efficacy results for a cohort of patients with relapsed/refractory MM who have received ≥12 cycles of treatment with vorinostat in combination with bortezomib. Methods Patients (aged ≥18 years) with relapsed or refractory MM (ECOG performance status 0-2) were sequentially enrolled on escalating doses of vorinostat combination therapy using a standard 3+3 design for ≤8 cycles. Cycles were repeated every 21 days and consisted of vorinostat 200 mg bid or 400 mg once daily (Days 1-14) in combination with bortezomib 0.7 or 0.9 mg/m2 i.v. on Days 4, 8, 11, and 15; or escalated to 0.9, 1.1, or 1.3 mg/m2 i.v. on Days 1, 4, 8, and 11. The addition of oral dexamethasone 20 mg on Days 1-4 and 9-12 of each cycle was permitted for disease progression (PD). Patients without disease progression at Cycle 8 were allowed to continue on study treatment. Results Of the 34 patients who have entered the study, 9 have received combined vorinostat and bortezomib treatment for ≥12 cycles and are the focus of this report. In this population, drug-related adverse events (AEs) occurred in 9/9 patients; 99% of these AEs were mild to moderate in severity (NCI Grade 1-3) and 6 patients had serious AEs (9 events). One patient experienced Grade 4 neutropenia, and 5 patients experienced Grade 3 drug-related AEs. The most common drug-related toxicities of any grade were diarrhea, nausea, and fatigue. The best responses observed in 9 evaluable patients were 5 partial response (duration 147 to 609 days), 2 minimal response (duration 42 to 161 days), and 2 stable disease (duration 371 to 742 days). Seven of 9 patients have now discontinued treatment; all due to progressive disease (median [range] time to progression was 294 days [42 to 742 days]). Conclusions These preliminary data indicate that extended treatment with vorinostat in combination with bortezomib (+/- dexamethasone) administered in a 21-day cycle shows significant long-term clinical activity with acceptable tolerability in patients with relapsed/refractory MM. Disclosures: Jagannath: Celgene: Honoraria; Millennium: Ad Board, Honoraria; Merck: Honoraria. Off Label Use: Vorinostat is a histone deacetylase (HDAC) inhibitor that was approved in the FDA in October 2006 for the treatment of cutaneous manifestations in patients with cutaneous T-cell lymphoma (CTCL) who have progressive, persistent, or recurrent disease on or following two systemic therapies. Weber:Millenium: Research Funding, Speakers Bureau; Celgene : Research Funding, Speakers Bureau; Merck : Research Funding, unpaid advisory board. Schiller:Denzyme: Research Funding; Cellegne: Research Funding; Eli Lilly: Research Funding; Centocor: Research Funding; Millennium: Research Funding, Speakers Bureau; Novartis: Research Funding, Speakers Bureau; Merck: Consultancy, Research Funding; Vion: Research Funding. Lupinacci:Merck: Employment, Equity Ownership. Reiser:Merck: Employment, Equity Ownership. Allen:Merck: Employment, Equity Ownership. Rizvi:Merck: Employment, Equity Ownership.

305 Background: Multiple myeloma (MM), the second most common hematologic malignancy, remains incurable despite recent therapeutic advances. Treatment of patients with relapsed and refractory MM is extremely challenging and represents a specific unmet medical need. However, novel treatment combinations have the potential to improve patient outcomes. Vorinostat, an oral inhibitor of Class I and II histone deacetylase enzymes, enhances the anti-MM activity of other pro-apoptotic agents, providing potential synergy in combination with lenalidomide and dexamethasone. This Phase I, multicenter, open-label, non-randomized, dose-escalation study evaluated vorinostat plus lenalidomide and dexamethasone in patients with relapsed or refractory MM. Aims: The primary objective was to determine the maximum tolerated dose (MTD); secondary objectives included overall safety and tolerability, and evaluation of clinical activity. Methods: Patients aged ≥18 years with relapsed or refractory MM were enrolled sequentially into 1 of 5 escalating dosing levels ([Table][1]) using a standard 3+3 design for ≤8 cycles. Patients who were tolerating, and receiving clinical benefit from, the regimen were allowed to continue into the extension phase of the study. In the absence of dose-limiting toxicities (DLTs) in the first cycle, dose escalation continued until the MTD was established. In the event that the MTD was not established, dose level 5 would become the maximum administered dose (MAD) and an additional 8 patients would be enrolled in an expansion cohort to confirm safety. Response to treatment was assessed using modified European Group for Blood and Marrow Transplantation (EBMT) criteria with the overall response rate (ORR) defined as minimal or greater, and all adverse events (AEs) recorded. | Dosing escalation | |:-----------------:| ---------------------------------------------------------------------- | | Dose level | Vorinostat dose (mg qd) 7 days on 7 days off (Days 1–7 and Days 15–21) | Lenalidomide dose (mg qd) × 21 days (Day 1 – Day 21) | Dexamethasone dose (mg qd) on Days 1, 8, 15, and 22 | Number of patients evaluable for DLTs | Number of treatment cycles to date | | 1 | 300 | 10 | 40 | 4 | ≤16 | | 2 | 400 | 10 | 40 | 4 | ≤14 | | 3 | 400 | 15 | 40 | 3 | ≤10 | | 4 | 400 | 20 | 40 | 3 | ≤9 | | 5 | 400 | 25 | 40 | 7 | ≤9 | | Expansion | 400 | 25 | 40 | 7 | ≤4 | * Cycles were repeated every 28 days and use of concomitant aspirin was recommended Results: Of 28 patients assessed for safety to date, all have experienced ≥1 AE, with 24 (87.5%) patients experiencing a total of 65 drug-related AEs overall, the majority of which were mild or moderate in severity. The most common drug-related AEs were diarrhea (n=12, 42.9%), fatigue (n=10, 37.5%), neutropenia (n=10, 37.5%), and thrombocytopenia (n=10, 37.5%). A total of 21 serious AEs, 8 of which were identified by the investigator as being related to study treatment, were reported in 13 (46.4%) patients. Three patients discontinued due to AEs. DLT evaluation is complete and there were no DLTs that prohibited dose escalation. One DLT, Grade 3 diarrhea lasting